WO2001095642A2 - A wireless location gateway and applications therefor - Google Patents
A wireless location gateway and applications therefor Download PDFInfo
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- WO2001095642A2 WO2001095642A2 PCT/US2001/017957 US0117957W WO0195642A2 WO 2001095642 A2 WO2001095642 A2 WO 2001095642A2 US 0117957 W US0117957 W US 0117957W WO 0195642 A2 WO0195642 A2 WO 0195642A2
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W88/00—Devices specially adapted for wireless communication networks, e.g. terminals, base stations or access point devices
- H04W88/005—Data network PoA devices
Definitions
- the present invention is directed generally to a system and method for locating people or objects, and in particular, to a system and 5 method for locating a wireless mobile station using a plurality of simultaneously activated mobile station location estimators.
- the present invention is directed generally to a system and method for locating people or objects, and in particular, to a system and method for locating a wireless mobile station using a plurality of mobile station location estimators. More generally, the present invention is l o directed to a computational system and method for calibrating the relative performance of multiple models, wherein each such model is capable of being activated for generating hypotheses (e.g., estimates and/or predictions) of an unknown condition such as the location of wireless mobile station.
- hypotheses e.g., estimates and/or predictions
- the present invention is directed to a computational system and method for generating enhanced hypotheses of the unknown condition, wherein the model generated hypotheses are used as queries into an archive that associates: (a) historical model generated hypotheses, (b) model input data used in generating the model hypotheses, and (c) verified hypotheses to which the model input data is known to
- wireless mobile 20 stations There is great interest in providing existing infrastructures for wireless communication systems with the capability for locating people and/or objects in a cost effective manner. Such a capability would be invaluable in a variety of situations, especially in emergency, ime situations and mobile commerce.
- wireless location technologies that purport to effectively locate wireless mobile 20 stations (as used herein this term includes, e.g., mobile phones, short message devices (SMS), electronic container tracking tags, micro-transceivers for personal location and/or emergency). These technologies an be generally classified as-.
- each such mobile station includes specialized electronics specifically for performing location.
- specialized electronics are for detecting and receiving satellite (or more generally, non-terrestrial) signals that can
- an alternative embodiment can be used to obtain an MS's locations.
- two different embodiments and/or techniques can be applied substantially simultaneously for locating an MS. In this latter case, a location resolver is likely needed to determine a "most likely" resulting MS l o location estimate.
- wireless location systems for combining wireless location techniques is described in the following international and U.S. patent applications which are each incorporated fully by reference herein: i. ⁇ .S. Provisional Application No.60/025,855 filed September 9, 1996 ii. U.S. Provisional Application No.60/044,821, filed April 25, 1997; iii. ⁇ .S. Provisional Application No.60/056,5 ( 10, filed August20, 1997; 15 iv. International Application No. P T/DS ⁇ s filed September 8, 1997 entitled "LOCATION OF A MOBILE
- a primary wireless location technique fails (e.g., due to an electronics malfunction), then assuming an alternative technique is available that does not use, e.g., the malfunctioning electronics of the primary technique, then the alternative technique can be used for MS location.
- the variety of wireless location techniques available is also problematic for at least the following reasons: 30 (a) a request for an MS location can require either the requester to know the wireless location service provider of the geographical area where the MS is likely to be, or to contact a location broker that is able to, e.g., determine a communication network covering the geographical area within which the MS is currently residing and activate (directly or through the MS's wireless service provider) an appropriate wireless location service.
- the technology enabling such a location broker capability has been referred to as a "wireless location gateway". An embodiment of such a gateway is described in the PCT/US97/15892 reference identified above;
- CMRS commercial radio service provider
- the plurality of location techniques may be.- activated according to any one or more of a number of activation strategies such as concurrent activation (e.g., for obtaining two location estimates of an MS location), data-driven activation (e.g., activated when appropriate input data is available), priority activation (e.g., an attempt to activate a preferred FOM is first performed, and if unsuccessful, or a result unsatisfactory, then an attempt at activating a second FOM is performed).
- concurrent activation e.g., for obtaining two location estimates of an MS location
- data-driven activation e.g., activated when appropriate input data is available
- priority activation e.g., an attempt to activate a preferred FOM is first performed, and if unsuccessful, or a result unsatisfactory, then an attempt at activating a second FOM is performed.
- Yet another object is to (or be able to) integrate into a wireless location gateway a large number of MS location techniques such as:
- timing advance techniques (2.2) timing advance techniques; (2.2) time-differe ⁇ ce-of-arrival wireless signal processing techniques; (23) adaptive wireless signal processing techniques having, for example, learning capabilities and including, for instance, artificial neural net and genetic algorithm processing;
- angle of arrival techniques (also denoted direction of arrival) for estimating an angle and/or direction of wireless signals transmitted from an MS
- Yet another object is to provide novel applications for wireless location that benefits from an integration of different location techniques.
- wireless herein is, in general, an abbreviation for "digital wireless", and in particular, “wireless” refers to digital radio signaling wa ⁇ one of standard ⁇ f>M protocols such as Advanced Mobile Phone Service (AMPS), Narrowband Mmce ⁇ Mobile Phone Service
- AMPS Advanced Mobile Phone Service
- NAMPS code division multiple access
- TDMA Time Division Multiple Access
- GSM Global Systems Mobile
- TDMA time division multiple access
- MS mobile station
- PS personal station
- U ⁇ location unit
- wireless infrastructure denotes one or more of: (a) a network for one or more of telephony communication services, (b) a collection of commonly controlled transceivers for providing wireless communication with a plurality of MSs, (c) the wireless Internet, (d) that portion of communications network that receives and processes wireless communications with wireless mobile stations.
- this infrastructure includes telephony wireless base stations (BS) such as those for radio mobile communication systems based on CDMA, AMPS, NAMPS, TDMA, and GSM wherein the base stations provide a network of cooperative communication channels with an air interface to the MS, and a conventional telecommunications interface with a Mobile Switch Center (MSC).
- BS telephony wireless base stations
- an MS user within an area serviced by the base stations may be provided with wireless communication throughout the area by user transparent communication transfers (i.e., "handoffs") between the user's MS and these base stations in order to maintain effective telephony service.
- the mobile switch center provides communications and control connectivity among base stations and the public telephone network.
- composite wireless signal characteristic values denotes the result of aggregating and filtering a collection of measurements of wireless signal samples, wherein these samples are obtained from the wireless communication between an MS to be located and the base station infrastructure (e.g., a plurality of networked base stations).
- the base station infrastructure e.g., a plurality of networked base stations.
- other phrases are also used herein to denote this collection of derived characteristic values depending on the context and the likely orientation of the reader.
- the phrase typically used is: "RF signal measurements”.
- location signature cluster and “location signal data” are used to describe signal characteristic values between the MS and the plurality of infrastructure base stations substantially simultaneously detecting MS transmissions.
- location communications between an MS and the base station infrastructure typically include simultaneous communications with more than one base station, a related useful notion is that of a "location signature” (also denoted “loc sig” herein) which is the composite wireless signal characteristic values for signal samples between an MS to be located and a single base station.
- the phrases: "signal characteristic values” or “signal characteristic data” are used when either or both a location signature ⁇ and/or a location signature clusters) are intended.
- the present invention relates to a method and system for performing wireless mobile station location.
- the present invention is a wireless mobile station location computing method and system that utilizes multiple wireless location computational estimators (these estimators also denoted herein as MS location hypothesizing computational models, "first order models", FOMs, and/or "location estimating models”), for providing location estimates of a target mobile station MS, wherein ambiguities and/or conflicts between the location estimates may be effectively and straightforwardly resolved.
- the present invention provides a technique for calibrating the performance of each of the location estimators so that a confidence value (e.g., a probability) can be assigned to each generated location estimate.
- a confidence value e.g., a probability
- the present invention provides a straightforward technique for using the confidence values (probabilities) for deriving a resulting most likely location estimate of a target wireless mobile station. More generally, the present invention relates to a novel computational method and architecture for synergistically combining the results of a plurality of computational models in a straightforward way that allows the models to be calibrated relative to one another so that differences in results generated by the models can be readily resolved. Accordingly, the computational method and architecture of the present invention may be applied to wide range applications where synergies between multiple models is expected to be enhance performance. 5 For a particular application having a plurality of computational models (each generating a hypothetical estimate of a desired result(s) in a space of hypothesis results), the present invention may be described, ata high level, as any method or system that performs the following steps:
- FAMs computational models
- the present step determines geographical subareas of a wireless network coverage area that have "similar" wireless signal characteristics. Such subareas may be relatively easy to determine, and there may be no constraint on the size of the subareas. The intention is to determine: (a) such a subarea as only a general area where a target MS must reside, and (b) the subarea should be
- (a) and (b) are believed to be substantially satisfied by grouping together into the same input class the wireless signal data sets (i.e., input data sets) from corresponding target MS locations wherein at each of the target MS locations: (i) the set of base stations detected by the target MS (at the location) is substantially the same, and/or (b) the set of base stations detecting the target MS is substantially the same set of base stations.
- the present step may be omitted.
- the calibrating of this step is performed using the input classification scheme determined in the above step (4.1.1).
- each model is supplied with inputs from a given fixed input class, 30 wherein each of these inputs have corresponding known results that constitute a correct hypothesis (i.e., a desired result).
- each model is determined for the input class and a confidence value is assigned to the model for inputs received from the input class.
- this procedure is repeated with each input class available from the input classification scheme.
- an application domain specific criteria is used to determine whether the hypotheses generated by the models identify the desired results in the hypothesis space. Accordingly, for each of the models, when supplied with an input data set from a fixed input class, the hypothesis generated by the model will be given tk confidence value determined for this input class as an indication of the likelihood of the generated
- the confidence value for each generated hypothesis may be computed as a probability that the hypothesis is correct.
- the criteria is whether a location hypothesis contains the actual location where the MS was when the corresponding input data set (wireless signal measurements) were communicated between this MS and the wireless network. l o
- this criteria may be whether an hypothesis identifies a proper functional unit such as a circuit board or chip.
- this criteria may be whether an hypothesis is within a particular range of the correct hypothesis. For example, if an application according to the present invention predicts the U.S. gross national product (GNP) six months into the future according to certain inputs (defining input data sets), then hypotheses
- the application specific criteria for this case may be that a generated hypothesis is within, say, ⁇ o% of the actual corresponding six month GNP prediction.
- the criteria may be whether an hypothesis actually identifies the object.
- the criteria may be whether an hypothesis provides a correct analysis.
- this step typically is performed at least once prior to inputting input data sets whose resulting hypotheses are to be used to determine the desired or correct results. Additionally, once an initial calibration
- this step may also be performed: (a) intermittently between the generation of hypotheses, and/or
- the present step provides an input data set including the composite signal characteristic values to one or more MS location hypothesizing computational models, wherein each such model subsequently determines one or more initial estimates (also denoted location hypotheses) of the location of the target MS. Note that one or more of these model may be based on, for example, the signal processing techniques 2.1 through 23 above.
- H.R is used as an index to retrieve other results from an archival database, wherein this database associates hypothesized results with their corresponding desired or correct results.
- H.R may be used to identify data from other archived hypothesized results that are "nearby" to HI, and subsequently use the nearby data to retrieve the corresponding desired results.
- the set of retrieved desired results may be used to define a new "adjusted" hypothesis.
- each location hypothesis, H identifies an area for a target MS, and H can used to identify additional related locations included in archived hypotheses generated by the same FOM as generated H.
- such related locations may be the area centroids of the archived hypotheses, wherein these centroids reside within the area hypothesized by H.
- centroids may be used to retrieve the corresponding actual verified MS locations (i.e., the corresponding desired results), and these retrieved verified locations may be used to generate a new adjusted area that is likely to be more accurate than H.
- a convex hull of the verified locations may be used as a basis for determining a new location hypothesis of the target MS.
- L H and AV chorus are associated in the data archive as a record of the vector gradient field.
- the adjustment technique includes a method for interpolating an adjustment at Lo from the verified adjustments at locations about Lo. Enhancements on such adjustment/interpolation techniques are also within the scope of the present invention.
- the weightings may be combined with other known wireless signal characteristics of the area such as an identification of: (a) a known sharp change in the geolocation gradient vector field, and/or (b) a subarea having reduced wireless transmission capabilities, and/or (c) a subarea wherein the retrieved records for the subarea have their estimates L View widely spaced apart, and/or (d) a subarea wherein there is an insufficient number of retrieved records.
- the present step requires a first technique to determine both "nearby" 5 archived data from previously archived hypotheses, and a second technique to determine an "adjusted" hypothesis from the retrieved desired results.
- such techniques can be relatively straightforward to provide when the hypothesized results reside in a vector space, and more particularly, in a Cartesian product of the real numbers. Accordingly, there are numerous applications that can be configured to generate hypothesized results in a vector space (or (artesian product of the real numbers).
- economic financial forecasting applications typically result in i o numeric predictions where the first and second techniques can be, e.g., substantially identical to the centroid and convex hull techniques for the wireless location application.; and (4.1.5)
- a step of subsequently computing a "most likely" target MS lo ⁇ tion estimate is computed, for outputting to a location requesting application such as 911 emergency, the fire or police departments, taxi services, etc. Note that in computing the most likely target MS lo ⁇ tion estimate a plurality of location hypotheses may be taken into account.
- the most likely MS location estimate is determined by computationally forming a composite MS location estimate utilizing such a plurality of location hypotheses so that, for example, lo ⁇ tion estimate similarities between location hypotheses can be effectively utilized.
- the confidence values are probabilities, an hypothesis may be generated that has a very low 0 (near zero) probability of having the desired result.
- H having a probability, P
- P there is a dual hypothesis H c that may be generated, wherein the H c represents the complementary hypothesis that the desired result is in the space of hypothesized results outside of H.
- the probability that the desired result(s) is outside of the result hypothesized by H is i-P.
- (4.13) as it relates to a wireless lo ⁇ tion system provided by the present invention, note that, it is an aspect of the present invention to provide location hypothesis enhancing and evaluation techniques that can adjust target MS location estimates according to historical MS lo ⁇ tion data and/or adjust the confidence values of location hypotheses according to how consistent the corresponding target MS location estimate is: (a) with historical MS signal characteristic values, (b) with various physical constraints, and (c) with various heuristics.
- the following capabilities are provided by the present invention:
- this data base may include: (a) a plurality of previously obtained lo ⁇ tio ⁇ signature clusters (i.e., composite wireless signal characteristic values) such that for each such cluster there is an associated actual or verified MS locations where an MS communi ⁇ ted with the base station infrastructure for locating the MS, and (b) previous MS location hypothesis estimates from FOM H derived from each of the lo ⁇ tion signature clusters stored according to (a).
- this data base include a location error gradient field for the know location errors for FOM H ;
- the composite signal characteristic values used to generate various location hypotheses for the target MS are compared against wireless signal data of known MS locations stored in the location signature data base for determining the reliability of the location hypothesizing models for particular geographic areas and/or environmental conditions; (53) a capability for reasoning about the likeliness of a location hypothesis wherein this reasoning capability uses heuristics and constraints based on physics and physical properties of the location geography; (5.4) an hypothesis generating capability for generating new location hypotheses from previous hypotheses.
- the present invention may utilize adaptive signal processing techniques.
- One particularly important utilization of such techniques includes the automatic tuning of the present invention so that, e.g., such tuning can be applied to adjusting the values of location processing system parameters that affect the processing performed by the present invention.
- location processing system parameters such system parameters as those used for determining the size of a geographi ⁇ l area to be specified when retrieving location signal data ofk ⁇ own MS locations from the historical (lo ⁇ tion signature) data base can substantially affect the lo ⁇ tion processing.
- a system parameter specifying a minimum size for such a geographical area may, if too large, cause unnecessary inaccuracies in locating an MS.
- an adaptation engine is included in the present invention for automatically adjusting or tuning parameters used by the present invention.
- the adaptation engine is based on genetic algorithm techniques.
- the present invention may include one or more FOMs that may be generally denoted as classification models wherein such FOMs are trained or calibrated to associate particular composite wireless signal characteristic values with a geographical lo ⁇ tion where a target MS could likely generate the wireless signal samples from which the composite wireless signal characteristic values are derived. Further, the present invention may include the capability for training and retraining such classification FOMs to automatically maintain the accuracy oftkit models even though substantial changes to the radio coverage area may occur, such as the construction of a new high rise building or seasonal variations (due to, for example, foliage variations). As used herein, "training” refers to iteratively presenting "training data" to a computational module for changing the behavior of the module so that the module may perform progressively better as it learns appropriate behavioral responses to the training data.
- training may include, for example, the repeated input of training data to an artificial neural network, or repeated statistical regression analyses on different and/or enhanced training data (e.g., statistical sample data sets).
- enhanced training data e.g., statistical sample data sets.
- the present invention may include a FOM(s) utilize multipath as an advantage for increasing accuracy.
- FOM(s) utilize multipath as an advantage for increasing accuracy.
- the utilization of classification FOMs in high multipath environments is especially advantageous in that high multipath environments are typically densely populated.
- high multipath environments are typically densely populated.
- training or calibration data captured by the present invention for training or calibrating such classification FOMs and for progressively improving the MS location accuracy of such models.
- classification FOMs may be utilized that determine target MS locations by correlating and/or associating network anomalous behavior with geographic locations where such behavior occurs. That is, network behaviors that are problematic for voice and/or data communication may be used advantageously for locating a target MS.
- network behaviors that are problematic for voice and/or data communication may be used advantageously for locating a target MS.
- wireless networks typically have within their coverage areas persistent subareas where voice quality is problematic due to, e.g., measurements related to high total errors, a high error rate, or change in error rate.
- such measurements may be related to frame error rates, redundancy errors, co-channel interference, excessive handoffs between base stations, and/or other call quality measurements.
- measurements may be used that are related to subareas where wireless communication between the network and a target MS is not sufficient to maintain a call (i.e., "deadzones").
- information about such so called problematic behaviors may be used by, e.g., a location estimator (FOM) to generate a more accurate estimate of a target MS.
- FAM location estimator
- network behavioral measurements may be provided for training an artificial neural network and/or for providing to a statistical regression analysis technique and/or statistical prediction models (e.g., using principle decomposition, partial leastsquares, or other regression techniques) for associating or correlating such measurements with the geographic area for which they likely derive.
- FOMs themselves may be hybrid combinations of MS location techniques.
- an embodiment of the present invention may include a FOM that uses a combination of Time Difference of Arrival (TDOA) and Timing Advance (TA) location measurement techniques for locating the target MS, wherein such a technique may require only minor modifications to the wireless infrastructure.
- TDOA Time Difference of Arrival
- TA Timing Advance
- such a FOM may provide reduced MS location errors and reduced resolution of ambiguities than are present when these techniques are used separately.
- Yost Model or FOM herein is disclosed in U.S. Patent 5,987329 filed July 30, 1997 and issued Nov.16, 1999 having Yost and Panc ⁇ apakesan as inventors, this patent being fully incorporated herein by reference.
- FOMs related to the Yost Model may also be incorporated into embodiments of the present invention wherein an elliptical search restriction location technique may also be utilized.
- an elliptical search restriction location technique may also be utilized.
- such a technique is disclosed in U.S. patent application, having U.S. Serial No.08/903,551, and entitled “System and Method Using Elliptical Search Area Coverage in Determining the Location of a Mobile Terminal", filed Jul.30, 1997, which is also incorporated by reference herein.
- LBS stationary, low cost, low power "location detection base stations”
- a grid of such LBSs n be utilized for providing wireless signaling characteristic data (from their built-in MSs) for: (a) (re)training such classification FOMs, and (b) calibrating the FOMs so that each generated lo ⁇ tion hypothesis has a reliable confidence value (probability) indicative of the likeliness of the target MS being in an area represented by the location hypothesis.
- the personal communication system (PCS) infrastructures currently being developed by telecommunication providers offer an appropriate localized infrastructure base upon which to build various personal location systems (PLS) employing the present invention and/or utilizing the techniques disclosed herein.
- the present invention is especially suitable for the location of people and/or objects using code division multiple access (CDMA) wireless infrastructures, although other wireless infrastructures, such as, time division multiple access (TDMA) infrastructures and GSM are also contemplated.
- CDMA code division multiple access
- TDMA time division multiple access
- GSM Global System for Mobile communications
- embodiments of the present invention may include components (e.g., FOMs) that an substantially automatically retrain themsilves to compensate for variations in wireless signal characteristics (e.g., multipath) due to environmental and/or topographic changes to a geographic area serviced by the present invention.
- the present invention optionally includes low cost, low power base stations, denoted location base stations (LBS) above, providing, for example, CDMA pilot channels to a very limited area about each such LBS.
- LBS location base stations
- the location base stations may provide limited voice traffic capabilities, but each is capable of gathering sufficient wireless signal characteristics from an MS within the location base station's range to facilitate locating the MS.
- the lo ⁇ tio ⁇ base stations by positioning the lo ⁇ tio ⁇ base stations at known locations in a geographic region such as, for instance, on street lamp poles and road signs, additional MS lo ⁇ tion accuracy an be obtained. That is, due to the low power signal output by such location base stations, for there to be signaling control communi ⁇ tion (e.g., pilot signaling and other control signals) between a lo ⁇ tion base station and a target MS, the MS must be relatively near the location base station. Additionally, for each location base station not in communication with the target MS, it is likely that the MS is not near to this location base station. Thus, by utilizing information received from both location base stations in communication with the target MS and those that are not in communication with the target MS, the present invention may substantially narrow the possible geographic areas within which the target MS is likely to be. Further, by providing each location base station (LBS) with a co-
- the stationary wireless transceiver (denoted a built-in MS above) having similar functionality to an MS, the following advantages are provided: (6. ⁇ ) assuming that the co-located base station capabilities and the stationary transceiver of an LBS are such that the base station capabilities and the stationary transceiver commu ⁇ i ⁇ te with one another, the stationary transceiver can be signaled by another components) of the present invention to activate or deactivate its associated base station capability, thereby conserving power for the LBS that operate on a restricted power juch as solar electrical power; l o (6.2) the stationary transceiver of an LBS can be used for transferring target MS location information obtained by the LBS to a conventional telephony base station;
- the present invention is able to (rejtrain itself in geographical areas having such LBSs. That is, by activating each LBS stationary transceiver so that there is signal communication between the stationary transceiver and surrounding base stations within range, wireless signal characteristic values for the location of the stationary
- such characteristic values can then be associated with the known lo ⁇ tion of the stationary transceiver for training various of the lo ⁇ tion processing modules of the present invention such as the classification FOMs discussed above.
- training and/or calibrating may include: (i) retraining FOMs; (ii) adjusting the confidence value initially assigned to a location hypothesis according to how accurate the generating FOM is
- One embodiment of the present invention utilizes a mobile (location) base station (MBS) that can be, for example, incorporated into a vehicle, such as an ambulance, police car, or taxi. Such a vehicle an travel to sites having a transmitting target MS, wherein such sites may be
- a mobile location base station as its name implies also includes base station electronics for communicating with mobile stations, though not necessarily in the manner of a conventional infrastructure base station.
- a mobile lo ⁇ tion base station may (in one embodiment) only monitor signal characteristics, such as MS signal strength, from a target MS without transmitting signals to the target MS.
- a mobile location base station can periodically be in bi-directional communication with a target MS for determining a signal time-of-arrival (or time-difference-of- arrival) measurement between the mobile location base station and the target MS.
- each such mobile location base station includes components for estimating the lo ⁇ tion of the mobile location base station, such mobile lo ⁇ tion base station location estimates being important when the mobile location base station is used for locating a target MS via, for example, time-of-arrival or time-difference-of-arrival measurements as one skilled in the art will appreciate.
- a mobile location base station can include: (7.1) a mobile station (MS) for both communicating with other components of the present invention (such as a location processing center included in the present invention); (7.2) a GPS receiver for determining a location of the mobile lo ⁇ tion base station;
- a mobile lo ⁇ tion base station includes modules for integrating or reconciling distinct mobile lo ⁇ tion base station location estimates that, for example, can be obtained using the components and devices of (7.1) through (7.4) above. That is, location estimates for the mobile location base station may be obtained from: GPS satellite data, mobile lo ⁇ tion base station data provided by the lo ⁇ tion processing center, dead reckoning data obtained from the mobile lo ⁇ tion base station vehicle dead reckoning devices, and location data manually input by an operator of the mobile location base station.
- the location estimating system of the present invention offers many advantages over existing location systems.
- the present invention employs a number of distinctly different location estimators which provide a greater degree of accuracy and/or reliability than is possible with existing wireless lo ⁇ tion systems.
- the location models provided may include not only the radius-radius/TOA and TDOA techniques but also adaptive techniques such as artificial neural net techniques and the techniques disclosed in the U.S. Patent 6,026304 by Hilsenrath et. al. incorporated by reference herein, and angle or direction of arrival techniques as well as substantially any other wireless location technique wherein appropriate input data can be obtained.
- various embodiments may provide various strategies for activating, within a single MS location instance, one or more location estimators (FOMs), wherein each such activated lo ⁇ tio ⁇ estimator is provided with sufficient wireless signal data input for the activation.
- one such strategy may be called “greedy” in that substantially as many location estimators may be activated as there is sufficient input (additionally, time and resources as well) for activation.
- some wireless lo ⁇ tion techniques are dependent on specialized location related devices being operational such as fixed or network based receivers, antennas, tranceivers, and/or signal processing equipment.
- location techniques also require particular functionality to be operable in the MS; e.g., functionality for detecting one or more location related signals from satellites (more generally non-terrestrial transmitting stations).
- the signals may be GPS signals.
- certain wireless lo ⁇ tion techniques may have their activations dependent upon whether such location related devices and/or MS functionality are available and operable for each instance of determining an MS location.
- location estimators may be activated according to the operable features present during an MS location instance for providing input activation data.
- the present invention may be able to adapt to environmental changes substantially as frequently as desired.
- the present invention may be able to take into account changes in the location topography over time without extensive manual data manipulation.
- the present invention an be utilized with varying amounts of signal measurement inputs.
- a location estimate is desired in a very short time interval (e.g., less than approximately one to two seconds)
- the present invention can be used with only as much signal measurement data as is possible to acquire during an initial portion of this time interval. Subsequently, after a greater amount of signal l o measurement data has been acquired, additional more accurate location estimates may be obtained.
- a first quick coarse wireless mobile station location estimate can be used to route a 911 call from the mobile station to a 911 emergency response center that has responsibility for the area containing the mobile station and the 911 caller. Subsequently, once the 911 all has been routed according to this first quick location estimate, by continuing to receive additional wireless signal measurements, more reliable and accurate location estimates of ⁇ it mobile station can be obtained.
- the location system of the present invention readily benefits from the distinct advantages of the CDMA spread spectrum scheme. Namely, these advantages include the exploitation of radio frequency spectral efficiency and isolation by (a) monitoring voice activity, (b) management of two-way power control, (c) provisioning of advanced variable-rate modems and error correcting signal encoding, (d) inherent resistance to fading, (e) enhanced privacy, and (f) multiple "rake" digital data receivers and searcher receivers for correlation of signal
- hypotheses may be generated by modular independent hypothesizing computational models (FOMs), wherein the FOMs 25 have been calibrated to thereby output confidence values (probabilities) related to the likelihood of correspondingly generated hypotheses being correct;
- FOMs modular independent hypothesizing computational models
- the location hypotheses from the FOMs may be further processed using additional amounts of application specific processing common or generic to a plurality of the FOMs;
- (8.1.3) tne computational architecture may enhance the hypotheses generated by the FOMs both according to past performance 30 of the models and according to application specific constraints and heuristics without requiring complex feedback loops for recalibrating one or more of the FOMs;
- the FOMs are relatively easily integrated into, modified and extracted from the computational architecture; (8.2) providing a computational paradigm for enhancing an initial estimated solution to a problem by using this initial estimated solution as, effectively, a query or index into an historical data base of previous solution estimates and corresponding actual solutions for deriving an enhanced solution estimate based on past performance of the module that generated the initial estimated solution.
- the multiple FOM architecture provided herein is useful in implementing solutions in a wide range of applications. In fact, most of the Detailed Description hereinbelow can be immediately translated into other application areas, as one skilled in the art of computer application architectures will come to appreciate. For example, the following additional applications are within the scope of the present invention:
- the domain wherein a diagnosis is to be performed has a canonical hierarchical order among the components within the domain.
- the components of an auto may be hierarchically ordered according to ease of replacement in combination within function.
- there may be a fuse box within an auto's electrical system (function)
- there will be fuses within the fuse box there will be fuses.
- these components may be ordered as follows (highestto lowest): auto, electrical system, fuse box, fuses.
- the confidence values for each component and its subcomponents maybe summed together to provide a likelihood value that the problem within the component. Accordingly, the lowest component having, for example, at least a minimum threshold of summed confidences can be selected as the most likely component for either further analysis and/or replacement. Note that such summed confidences may be normalized by dividing by the number of hypotheses generated from the same input so that the highest summed confidence is one and the lowest is zero. Further note that this example is merely representative of a number of different diagnosis and/or prediction applications to which the present invention is applicable, wherein there are components that have canonical hierarchical decompositions.
- a technique similar to the auto illustration above may be provided for the diagnosis of computer systems, networks (LANs, WANs, Internet and telephony networks), medical diagnosis from, e.g., x-rays, MRIs, sonograms, etc;
- robotics applications such as scene and/or object recognition. That is, various FOMs may process visual image input differently, and it may be that for expediency, an object is recognized if the summed confidence values for tk object being recognized is above a certain threshold ; (9.4) seismic and/or geologic signal processing applications such as for locating oil and gas deposits;
- this architecture need not have all modules co-located.
- various modules can be remotely lo ⁇ ted from one another and communicate with one another via telecommuni ⁇ tion transmissions such as telephony technologies and/or the Internet.
- the present invention is particularly adaptable to such distributed computing environments.
- some number of the first order models may reside in remote locations and com uni ⁇ te their generated hypotheses via the Internet.
- the processing following the generation of location hypotheses (each having an initial location estimate) by the first order models may be such that this processing an be provided on Internet user nodes and the first order models may reside at Internet server sites. In this configuration, an Internet user may request hypotheses from such remote first order models and perform the remaining processing at his/her node.
- central location development sites may be networked to, for example, geographically dispersed location centers providing lo ⁇ tion services according to the present invention, wherein the FOMs may be accessed, substituted, enhanced or removed dynamically via network connections (via, e.g., the Internet) with a central location development site.
- a small but rapidly growing municipality in substantially flat low density area might initially be provided with access to, for example, two or three FOMs for generating lo ⁇ tion hypotheses in the municipality's relatively uncluttered radio signaling l o environment.
- additional or alternative FOMs may be transferred via the network to the lo ⁇ tion center for the municipality.
- the FOMs can be incorporated into an expert system, if desired.
- each FOM may be activated from an antecedent of an expert system rule.
- the antecedent for such a rule can be activated from an antecedent of an expert system rule.
- the FOM 15 evaluate to TRUE if the FOM outputs a location hypothesis, and the consequent portion of such a rule may put the output lo ⁇ tion hypothesis on a list of location hypotheses occurring in a particular time window for subsequent processing by the location center.
- activation of the FOMs may be in the consequents of such expert system rules. That is, the antecedent of such an expert system rule may determine if the conditions are appropriate for invoking the FOM(s) in the rule's consequent.
- the present invention may also be configured as a blackboard system with intelligent agents (FOMs).
- FAMs intelligent agents
- intelligent agents is calibrated using archived data so that for each of the input data sets provided either directly to the intelligent agents or to the blackboard, each hypothesis generated and placed on the blackboard by the intelligent agents has a corresponding confidence value indicative of an expected validity of the hypothesis.
- the FOMs may be object methods on an MS lo ⁇ tion estimator object, wherein the estimator objectt receives substantially all target MS location signal data output by the signal filtering subsystem.
- software bus architectures are contemplated by the present invention, as one skilled in the art will understand, wherein the software architecture may be modular and facilitate parallel processing.
- Fig.2 shows aspects of the two-ray radio propagation model and the effects of urban clutter.
- Fig.3 provides a typical example of how the statistical power budget is calculated in design of a Commercial Mobile Radio Service 5 Provider network.
- Fig.4 illustrates an overall view of a wireless radio location network architecture, based on advanced intelligent network (AIN) principles.
- AIN advanced intelligent network
- Fig.5 is a high level block diagram of an embodiment of the present invention for locating a mobile station (MS) within a radio coverage area for the present invention.
- l o Fig.6 is a high level block diagram of the location cente ⁇ zp.
- Fig.7 is a high level block diagram of the hypothesis evaluator for the location center.
- Fig.8 is a substantially comprehensive high level block diagram illustrating data and control flows between the components of (and/or accessed by) the location center/gateway 142, as well the functionality of these components.
- Figs.9A and 9B are a high level data structure diagram describing the fields of a location hypothesis object generated by the fi ⁇ t 15 order models 1224 of the location center.
- Fig. to is a graphi ⁇ l illustration of the computation performed by the most likelihood estimator 1344 of the hypothesis evaluator.
- Fig. n is a high level block diagram of the mobile base station (MBS).
- Fig.12 is a high level state transition diagram describing computational states the Mobile Base station enters during operation.
- Fig.13 is a high level diagram illustrating the data structural organization of the Mobile Base station capability for autonomously 20 determining a most likely MBS location from a plurality of potentially conflicting MBS lo ⁇ tion estimating sources.
- Fig.14 illustrates the primary components of the signal processing subsystem.
- Fig.15 illustrates how automatic provisioning of mobile station information from multiple CMRS occurs.
- Fig.16 illustrates another embodiment of the location engine 139, wherein the context adjuster 1326 (denoted in this figure as “lo ⁇ tion hypothesis adjuster modules”) includes a module (1436) that is capable of adjusting lo ⁇ tion hypotheses for reliability, and another 5 module (1440) that is capable of adjusting location hypotheses for accuracy.
- the context adjuster 1326 includes a module (1436) that is capable of adjusting lo ⁇ tion hypotheses for reliability, and another 5 module (1440) that is capable of adjusting location hypotheses for accuracy.
- Fig.17 illustrates the primary components of the signal processing subsystem.
- Fig.18 is a block diagram further illustrating the present invention as a wireless location gateway.
- Fig.19 is a block diagram of an electronic networked yellow pages for providing intelligent advertising services, wherein wireless location services may be utilized.
- Fig.4 is a high level diagram of one embodiment of a wireless radiolocation architecture for the present invention. Accordingly, this figure illustrates the interconnections between the components of a wireless cellular communication network, such as, a typical PCS network configuration and various components that are specific to the present invention.
- a typical wireless (PCS) network includes:
- MSs 140 for at least one of voice related communication, visual (e.g., text such as is provided by a short message service) related communication, and according to present invention, location related communication.
- voice related communication e.g., voice related communication
- visual (e.g., text such as is provided by a short message service) related communication e.g., text such as is provided by a short message service) related communication
- location related communication e.g., location related communication.
- some of the MSs 140 may include the electronics and corresponding software to detect and process signals from non-terrestrial transmission stations such as GPS and/or GLONASS satellites.
- non- terrestrial transmission stations an also be high attitude aircraft which, e.g., can hover over a metropolitan area thereby facilitating wireless communications;
- each cell site includes an infrastructure base station such as those labeled 122 (or variations thereof such as 122A - 122b).
- the base stations 122 denote the standard high traffic, fixed location base stations used for voice and data communication with a plurality of MSs 140, and, according to the present invention, also used for communication of information related to locating such MSs 140.
- the base stations labeled 152 are more directly related to wireless location enablement.
- the base stations 152 may be low cost, low functionality transponders that are used primarily in communicating MS location related information to the location center 142 (via base stations 122 and the MSC 112).
- the base stations 152 will be referred to hereinafter as location base stations) 152 or simply LBS(s) 152;
- a public switched telephone network (PSTN) 124 (which may include signaling system links 106 having network control components such as: a service control point (SCP) 104 , one or more signaling transfer points (STPs) no.
- PSTN public switched telephone network
- SCP service control point
- STPs signaling transfer points
- the present invention provides one or more location centers/gateways 142. Such gateways may be described at a high level as follows.
- a location center/gateway 142 (also be referred to as a location center/gateway, or simply gateway) , in response to a location request received at the location center, an request activation of one or more of a plurality of wireless location techniques in order to locate an MS 140.
- Fig.18 is block diagram illustrating another embodiment of the location center/gateway 142 of the present invention.
- the wireless location gateway artivation requests may be dependentupon, e.g.,
- a wireless network with which the MS 140 may be in contact such a network may be:
- a commercial mobile radio network supporting telephony functionality (i) a commercial mobile radio network supporting telephony functionality, (ii) a short messaging service or paging network; (iii) a wireless network of beacons for providing location related information such as GPS and LORAN C,
- wireless carrier independent networks for performing wireless location such as the wireless location network provided by Times Three, Suite #220, Franklin Atrium, 30155th Avenue N.E,. Calgary, AB T2A
- a wireless broadcasting network for use in activating an MS 140 of, e.g., a stolen vehicle such as is provided by LoJack Corporation, 333 Elm Street, Dedham, MA 02026, and/or
- the location signal measurement obtaining capabilities of the wireless network with which the MS may be in contact may only support a network centric location technique;
- the functionality of the MS 140 such as: the type(s) of wireless signals which can be detected and processed by the MS such as.- (i) non-terrestrial signals such as GPS signals,
- the location service provider contacted by the gateway 142 may be different from the location service provider if the MS is likely to be in the U.S.
- these techniques may be co-located with the gateway, accessible via a network including: (i) local area networks, and (ii) wide area networks such as a telephony (wired or wireless) network, the Internet or a cable network.
- the gateway 142 may supply to one or more of the location estimators, measurements of communications between the MS 140 and one or more networks for determining a location of the MS 140.
- the gateway 142 may provide, with the location activation request, an identification of where the measurements may be obtained (e.g., one or more network addresses).
- such a gateway 142 may also send requests) to the networks) having such MS communication measurements to forward them to particular location estimators. Note, that in performing these tasks, the gateway 142 may receive with a location request (or may retrieve in response thereto) information regarding the functionality of the target MS 140, e.g., as discussed above.
- the gateway 142 may be the intermediary between location requesting applications and the location estimators, thereby providing a simple, uniform application programming interface (API) for such applications substantially independently of the lo ⁇ tion estimators that are activated to fulfill such location requests.
- API application programming interface
- the gateway 142 (or embodiments thereof) can substantially ease the burden on geolocation service providers by providing a substantially uniform method for obtaining target MS/network signal data for use in locating the target MS.
- a location service provider may substantially reduce the number and complexity of its data exchange interfaces with the wireless networks for obtaining target MS/network signal data.
- the networks capturing such signal data may also reduce the complexity and number of their interfaces for providing such signal data to lo ⁇ tion service providers.
- the gateway may also fulfill location requests wherein the location is for a stationary and/or wireline handset instead of a mobile station 140. Accordingly, the gateway 142 may request access to, e.g., phone lo ⁇ tion information stored in a ⁇ rrier's database of premise provisioning equipment as one skilled in the art will understand.
- the gateway 142 may also facilitate in the providing of certain lo ⁇ tion related services in addition to providing, e.g., MS 140 locations.
- one or more of the following location related services may be facilitated by the gateway 142 or may be made operative via the wireless location capabilities of the gateway 142.
- the following location related services can, in general, be provided without use of a gateway 142, albeit, e.g., in a likely more restricted context wherein not all available wireless location estimating techniques are utilized, and/or by multiplying the number of interfaces to geolocation service providers (e.g., distinct wireless location interfaces provided directly to each wireless lo ⁇ tion service provider utilized). Further note that at some of these applications are described in greater detail in later sections herein:
- gateway 142 may cooperate with an automated speech recognition interpretation and synthesis unit for providing substantially automated interactive communi ⁇ tion with an MS 140 for providing spoken directions. Note that such directions may be provided in terms of street names and/or descriptions of the terrain (e.g., "the glass high rise on the left having pink tinted glass").
- Advertising may be directed to an MS 140 according to its location.
- MS 140 users do not respond well to unsolicited wireless advertisement whether location based or otherwise.
- certain advertisements may be viewed in a more friendly light.
- an MS user may contact, e.g., a wireless advertising portal by voice or via wireless Internet, and describe certain merchandise desired (e.g., via interacting with an automated speech interaction unit) the user may be able to describe and receive (at his/her MS 140) visual displays of merchandise that may satisfy such a user's request. For example, an MS user may provide a spoken request such as: "I need a shirt, who has specials near here?".
- various architectures for the location center/location gateway are within the scope of the invention including a distributed architecture wherein in addition to the FOMs being possibly remotely accessed (e.g., via a communications network such as tk Internet), the gateway itself may be distributed throughout one or more communication networks.
- a location request received at a first location gateway portion may be routed to a second location gateway portion (e.g., via the Internet).
- Such a distributed gateway may be considered a "meta-gateway" and in fact such gateway portions may be fully functioning gateways in their own right. Thus, such routing therebetween may be due to contractual arrangements between the two gateways (each fulfilling location requests for a different network, wireless carrier, and/or geographical region).
- a given lo ⁇ tion gateway may provide lo ⁇ tion information for only certain areas corresponding, e.g., to contractual arrangements with the wireless carriers with which the location gateway is affiliated.
- a first lo ⁇ tion gateway may provide vehicle locations for a first collection of one or more wireless networks
- a second location gateway may provide vehicle locations for a second collection of one or more wireless networks.
- the first gateway may be initially contacted for determining whether the vehicle an be looted via communications with the first collection of one or more wireless networks, and if the vehicle an not be loated, the first gateway may provide a location request to the second gateway for thereby lo ⁇ ting the stolen vehicle via wireless communications with one or more wireless networks of the second collection. Furthermore, the first gateway may provide location requests for the stolen vehicle to other location gateways.
- the present invention provides the following additional components:
- MBS mobile base stations 148
- LBS location base stations 152
- LBS 152 having a relatively small MS 140 detection area 154.
- LBSs 152 may also support Internet and/or TCP/IP transmissions for transmitting visual location related information (e.g., graphical, or pictorial) related to an MS location request.
- visual location related information e.g., graphical, or pictorial
- lo ⁇ tion base stations 152 can be lo ⁇ ted on, e.g, each floor of a multi-story building, the wireless location technology described herein can be used to perform location in terms of height as well as by latitude and longitude.
- an MS 140 may utilize one or more of the wireless technologies, CDMA, TDMA, AMPS, NAMPS or GSM for wireless communi ⁇ tion with: (a) one or more infrastructure base stations 122, (b) mobile base s ⁇ tion(s) 148, or (c) an LBS 152. Additionally, note that in some embodiments of the invention, there may be MS to MS communication.
- BSs Three exemplary base stations (BSs) are 122A, 1226 and 122C, each of which radiate referencing signals within their area of coverage 169 to facilitate mobile station (MS) 140 radio frequency connectivity, and various timing and synchronization functions.
- MS mobile station
- some base stations may contain no sectors 130 (e.g.122E), thus radiating and receiving signals in a 360 degree omnidirectional coverage area pattern, or the base station may contain "smart antennas" which have specialized coverage area patterns.
- the generally most frequent base stations 122 have three sector 130 coverage area patterns.
- base station 122A includes sectors 130, additionally labeled a, b and c. Accordingly, each of the sectors 130 radiate and receive signals in an approximate 120 degree arc, from an overhead view.
- actual base station coverage areas 169 (stylisti ⁇ lly represented by hexagons about the base stations 122) generally are designed to overlap to some extent, thus ensuring seamless coverage in a geographical area.
- Control electronics within each base station 122 are used to communi ⁇ te with a mobile stations 140.
- Information regarding the coverage area for each sectori3o such as its range, area, and "holes" or areas of no coverage (within the radio coverage area 120), may be known and used by the location centers to facilitate location determination.
- each base station 122 communicating with the MS 140 as well, as any sector identifi ⁇ tion information may be known and provided to the location center 142.
- a base station or mobility controller 174 controls, processes and provides an interface between originating and terminating telephone calls from/to mobile station (MS) 140, and the mobile switch center (MSC) 112.
- the MSC 122 on-the-other-hand, performs various administration functions such as mobile station 140 registration, authentication and the relaying of various system parameters, as one skilled in the art will understand.
- the base stations 122 may be coupled by various transport facilities 176 such as leased lines, frame relay, T-Carrier links, optical fiber links or by microwave communication links.
- an MS 140 When an MS 140 is powered on and in the idle state, it constantly monitors the pilot signal transmissions from each of the base stations 122 located at nearby cell sites. Since base station/sector coverage areas may often overlap, such overlapping enables an MS 140 to detect, and, in the case of certain wireless technologies, communicate simultaneously along both the forward and reverse paths, with multiple base stations 122 and/or sectors 130. In Fig.4, the constantly radiating pilot signals from base station sectors 130, such as sectors a, b and c of BS 122A, are detectable by MSs 140 within the coverage area 169 for BS 122A.
- the mobile stations 140 scan for pilot channels, corresponding to a given base station/sector identifiers (IDs), for determining in which coverage area 169 (i.e., cell) it is contained. This is performed by comparing signal strengths of pilot signals transmitted from these particular cell-sites.
- IDs base station/sector identifiers
- the mobile station 140 then initiates a registration requestwith the MSC 112, via the base station controller 174.
- the MSC 112 determines whether or not the mobile station 140 is allowed to proceed with the registration process (except, e.g., in the case of a 911 call, wherein no registration process is required). Once any required registration is complete, calls may be originated from the mobile station 140 or calls or short message service messages can be received from the network.
- the MSC 112 communicates as appropriate, with a class 4/5 wireline telephony circuit switch or other central offices, connected to the PSTN 124 network. Such central offices connect to wireline terminals, such as telephones, or any communication device compatible with a wireline.
- the PSTN 124 may also provide connections to long distance networks and other networks.
- the MSC 112 may also utilize IS/41 data circuits or trunks connecting to signal transfer point no, which in turn connects to a service control point 104, via Signaling System #7 (SS7) signaling links (e.g., trunks) for intelligent call processing, as one skilled in the art will understand.
- SS7 Signaling System #7
- Such links are used for call routing instructions of calls interacting with the MSC 112 or any switch capable of providing service switching point functions, and the public switched telephone network (PSTN) 124, with possible termination back to the wireless network.
- PSTN public switched telephone network
- the location center/gateway (L() 142 interfaces with the MSC 112 either via dedi ⁇ ted transport facilities 178, ling, e.g., any number of LAN/WAN technologies, such as Ethernet, fast Ethernet, frame relay, virtual private networks, etc., or via the PSTN 124.
- the gateway 142 may receive autonomous (e.g., unsolicited) command/response messages regarding, for example: (a) the state of the wireless network of each commercial radio service provider utilizing the LC 142 for wireless lo ⁇ tion services, (b) MS 140 and BS 122 radio frequency (RF) measurements, (c) communications with any MBSs 148, and (d) location applications requesting MS locations using the lo ⁇ tion center/gateway 142.
- autonomous (e.g., unsolicited) command/response messages regarding, for example: (a) the state of the wireless network of each commercial radio service provider utilizing the LC 142 for wireless lo ⁇ tion services, (b) MS 140 and BS 122 radio frequency (
- the LC 142 may provide data and control information to each of the above components in (a) - (d). Additionally, the LC 142 may provide location information to an MS 140, via a BS 122. Moreover, in the case of the use of a mobile base station (MBS) 148, several communications paths may exist with the LC 142.
- MBS mobile base station
- the MBS 148 may act as a low cost, partially-functional, moving base station, and is, in one embodiment, situated in a vehicle (e.g., land, water or aircraft) where an operator may engage in MS 140 searching and tracking activities. In providing these activities using CDMA, the MBS 148 provides a forward link pilot channel for a target MS 140, and subsequently receives unique BS pilot strength measurements from the MS 140.
- the MBS 148 also includes a mobile station 140 for data communication with the gateway 142, via a BS 122.
- such data communi ⁇ tion includes telemetering at least the geographic position (or estimates thereof) of the MBS 148, various RF measurements related to signals received from the target MS 140, and in some embodiments, MBS 148 estimates of the location of the target MS 140.
- the MBS 148 may utilize multiple-beam fixed antenna array elements and/or a oveable narrow beam antenna, such as a microwave dish 182.
- the antennas for such embodiments may have a known orientation in order to further deduce a radio location of the target MS 140 with respect to an estimated current location of the MBS 148.
- the MBS 148 may further contain a satellite (eg., global positioning system (GPS)) receiver (or other receiver for non-terrestrial wireless signals) for determining the location of the MBS 148 and/or providing wireless location assistance a target MS 140, e.g, providing GPS information to the MS to assist the MS in determining its location.
- the MBS 148 may include distance sensors, dead-reckoning electronics, as well as an on-board computing system and display devices for locating both the MBS 148 itself as well as tracking and locating the target MS 140.
- the computing and display provides a means for communicating the position of the target MS 140 on a map display to an operator of the MBS 148. It is important to note that in one embodiment, an MBS 148 may determine its location substantially independent of the communications networks) with which the MBS
- Each lo ⁇ tion base station (LBS) 152 is a low cost location device.
- each LBS 152 only partially or minimally supports the air-interface standards of the one or more wireless technologies used in communicating with both the BSs 122 and the MSs 140.
- Each LBS 152 when put in service, is placed at a fixed location, such as at a traffic signal, lamp post, etc., wherein the location of the LBS may be determined as accurately as, for example, the accuracy of the locations of the infrastructure BSs 122.
- a fixed location such as at a traffic signal, lamp post, etc.
- the location of the LBS may be determined as accurately as, for example, the accuracy of the locations of the infrastructure BSs 122.
- CDMA the wireless technology
- each BS 122 uses a time offset of the pilot PN sequence to identify a forward CDMA pilot channel.
- each LBS 152 emits a unique, time-offset pilot PN sequence channel in accordance with the (DMA standard in the RF spectrum designated for BSs 122, such that the channel does not interfere with neighboring BSs 122 cell site channels, and does not interfere with neighboring LBSs 152.
- Each LBS 152 may also contain multiple wireless receivers in order to monitor transmissions from a target MS 140.
- each LBS 152 contains mobile station 140 electronics, thereby allowing the LBS to both be controlled by, e.g., the gateway 142 or the wireless carriers) for the LBS, and to transmit information to, e.g., the gateway 142 (via, e.g., at least one neighboring BS 122), or to another wireless location service provider such as one providing one or more FOMs.
- the gateway 142 may request lo ⁇ tion information about the target MS 140 from, for instance, one or more activated LBSs 152 in a geographical area of interest.
- the LBS's pilot channel appears to the target MS 140 as a potential neighboring base station channel, and consequently, is placed, for example, in the (DMA neighboring set, or the (DMA remaining set of the target MS 140 (as one familiar with the (DMA standards will understand).
- the target MS 140 will, if within range of such an activated LBS 152, detect the LBS pilot presence during the (DMA pilot channel acquisition substate. Consequently, the target MS 140 performs RF measurements on the signal from each detected LBS 152. Similarly, an activated LBS 152 an perform RF measurements on the wireless signals from the target MS 140. Accordingly, each LBS 152 detecting the target MS 140 may subsequently telemeter back to the LC 142 measurement results related to signals from/to the target MS 140.
- the target MS 140 may telemeter back to the gateway 142 its own measurements of the detected LBSs 152, and consequently, this new location information, in conjunction with lo ⁇ tion related information received from the BSs 122, can be used to locate the target MS 140.
- an LBS 152 will normally deny hand-off requests, since typically the LBS does not require the added complexity of handling voice or traffic bearer channels, although economics and peak traffic load conditions may dictate preference here.
- GPS timing information needed by any CDMA base station, is either achieved via a the inclusion of a lo ⁇ l GPS receiver or via a telemetry process from a neighboring conventional BS 122, which contains a GPS receiver and timing information. Since energy requirements are minimal in such an LBS 152, (rechargeable) batteries or solar cells may be used to power the LBSs. Further, no expensive terrestrial transport link is typi ⁇ lly required since two-way communication is provided by an included MS 140 (or an electronic variation thereof) within each LBS. Thus, LBSs 152 may be placed in numerous locations, such as:
- a lo ⁇ tion application programming interface 136 (Fig.4), denoted L-API, is may be provided between the lo ⁇ tion center/gateway 142 (LC) and the mobile switch center (MSC) network element type, in order to send and receive various control, signals and data messages.
- the L-API may be implemented using a preferably high-capacity physical layer communications interface, such as IEEE standard 802.30° baseT Ethernet), although other physi ⁇ l layer interfaces could be used, such as fiber optic ATM, frame relay, etc.
- At least two forms of L-API implementation are possible. In a first ⁇ se, the signal control and data messages are provided using the MSC 112 vendor's native operations messages inherent in the product offering, without any special modifications. In a second case, the L-API includes a full suite of commands and messaging content specifi ⁇ lly optimized for wireless lo ⁇ tion purposes, which may require some, although minor development on the part of an MSC vendor. Signal Processor Description
- a signal processing subsystem (labeled 1220 in other figures) may be provided (or accessed) by the gateway 142. Such a signal processing subsystem may: (a) receive control messages and signal measurements from one or more wireless service provider networks, and (b) transmit appropriate control messages to such wireless networks via the location applications programming interface 136 referenced earlier, for wireless location purposes.
- the signal processing subsystem 1220 additionally provides various signal identification, conditioning and pre-processing functions, including buffering, signal type classification, signal filtering, message control and routing functions to the lo ⁇ tion estimating modules or FOMs .
- a mobile station 140 (Fig. l) may be able to detect up to three or four pilot channels representing three to four base stations, or as few as one pilot channel, depending upon the environment and wireless network configuration.
- possibly more than one BS 122 can detect a mobile station 140 transmitter signal, and the fact that multiple (MRS' base station equipment commonly will overlap coverage areas.
- the "first" finger represents the most direct, or least delayed multipath signal.
- Second or possibly third or fourth fingers may also be detected and tracked, assuming the detecting base station and/or mobile station 140 contains a sufficient number of data receivers for doing so.
- the signal processing subsystem may utilize various wireless signal measurements of transmissions between a target mobile station 140 and a network of base stations 122, 152 and/or 148.
- Such measurements can be important in effectively estimating the location of mobile stations 140 in that it is well known that measurements of wireless signal propagation characteristics, such as signal strength (e.g., RSSI), time delay, angle of arrival, and any number other measurements, can individually lead to gross errors in MS 140 location estimates.
- signal strength e.g., RSSI
- time delay e.g., time delay
- angle of arrival e.g., angle of arrival
- one aspect of the present invention is directed to utilizing a larger number of wireless signal measurements, and utilizing a plurality of MS 140 estimation techniques to compensate for location estimation errors generated by some such techniques.
- most practical digital P(S deployments result in fewer than three base station pilot channels being reportable in the majority of lo ⁇ tion areas, thus resulting in a larger, more amorphous location estimates by terrestrial triangulation systems.
- additional location enhancements n be obtained. For example, by enhancing a mobile station 140 with electronics for detecting satellite transmissions (as done with mobile base stations 148 and which also an be viewed as such an enhanced mobile station 140) additional location related signals maybe obtained from:
- GLONASS Global Navigation Satellite System
- LEOs low earth orbit satellite systems
- MEOs medium earth orbit satellite systems
- the transmissions from the MS 140 used for determining the MS's location need not be transmitted to terrestrial base stations (e.g., 122). It is within the scope of the present invention that a target MS 140 may transmit location related information to satellites as well. For example, if a target MS 140 detects two GPS satellite transmissions and is able to subsequently transmit the GPS signal measurements (e.g., timing measurements) to an additional satellite capable of determining additional MS lo ⁇ tion measurements according to the signals received, then by performing a triangulation process at the location center/gateway 142 (which may be co-located with the additional satellite, or at a remote terrestrial site), a potentially reliable and accurate MS location an be obtained.
- GPS signal measurements e.g., timing measurements
- the present invention is ⁇ pable of resolving wireless location ambiguities due to a lack of location related information of one type by utilizing supplemental location related information of a different type.
- type as used here it is intended to be interpreted broadly as, e.g.,
- wireless networks based on different wireless signaling technologies may be used to locate an MS 140 during the time period of a single emergency all such as E911.
- the target MS 140 may use one or more of a plurality of wireless communi ⁇ tion networks, possibly based on differentwireless communication technologies, depending on availability the of technology in the coverage area.
- dual mode or “tri-mode” mobile stations 140 are available, wherein such mobile stations are ⁇ pable of wireless communication in a plurality of wireless communication technologies, such as digital (e.g., CDMA, and/or TDMA) as well as analog or AMP/NAMPS, such mobile stations may utilize a first (likely a default) wireless communi ⁇ tion technology whenever possible, but switch to another wireless communi ⁇ tion technology when, e.g., coverage of the first wireless technology becomes poor.
- first wireless communi ⁇ tion technology likely a default wireless communi ⁇ tion technology whenever possible, but switch to another wireless communi ⁇ tion technology when, e.g., coverage of the first wireless technology becomes poor.
- the present invention may include (or access) FOMs for providing mobile station lo ⁇ tion estimates wherein the target MS 140 communi ⁇ tes with various networks using different wireless communi ⁇ tion technologies.
- FOMs may be activated according to the wireless signal measurements received from various wireless networks and/or wireless technologies supported by a target MS 140 and to which there is a capability of communicating measurements of such varied wireless signals to the FOM(s).
- the MS may, if there is overlapping coverage of two wireless communication technologies and the MS supports communications with both, repeatedly switch back and forth between the two thereby providing additional wireless signal measurements for use in locating the target MS 140.
- FOMs may be activated substantially simultaneously (or alternatively, wherever appropriate input is received that allow particular FOMs to be activated).
- the FOMs may provide "inverse" estimates of where a target MS 140 is not instead of where it is.
- Such inverse analysis can be very useful in combination with lo ⁇ tion estimates indicating where the target MS is in that the accuracy of a resulting MS location estimate may be substantially decreased in size when such inverse estimates are utilized to rule out areas that otherwise appear to be likely possibilities for containing the target MS 140.
- a FOM that can provide such reverse analysis is a location computational model that generates target MS lo ⁇ tion estimates based on archived knowledge of base station coverage areas (such an archive being the result of, e.g., the compilation a RF coverage database - either via RF coverage area simulations or field tests).
- a model may provide target MS location inverse estimates having a high confidence or likelihood that that the target MS 140 is not in an area since either a base station 122 (or 152) an not detect the target MS 140, or the target MS can not detect a particular base station.
- the confidences or likelihoods on such estimates may be used by diminishing a likelihood that the target MS is in an area for the estimate, or alternatively the confidence or likelihood of all areas of interest outside of the estimate n increased.
- both measurements of forward wireless signals to a target MS 140, and measurements of reverse wireless signals transmitted from the target MS to a base station an be utilized by various FOMs.
- the received relative signal strength (RRSS BS ) of detected nearby base station transmitter signals along the forward link to the target mobile station can be more readily used by the location estimate modules (FOMs) since the transmission power of the base stations 122 typically changes little during a communication with a mobile station.
- the relative signal strength (RRSS of target mobile station transmissions received by the base stations on the reverse link may require more adjustment prior to lo ⁇ tion estimate model use, since the mobile station transmitter power level changes nearly continuously.
- the lo ⁇ tion center/gateway 142 computes (or requests computation of) location estimates for a wireless mobile station 140 by performing at least some of the following steps: (23.0) receiving an MS location request; (23.1) receiving measurements of signal transmission characteristics of communications communicated between the target MS 140 and one or more wireless infrastructure base stations 122. Note, this step may only be performed if the gateway provides such measurements to a FOM (e.g perhaps a FOM co-lo ⁇ ted therewith);
- this step may also only be performed if the gateway provides such measurements to a FOM. Otherwise, such FOM is likely to perform such filtering;
- MS is lo ⁇ ted in the lo ⁇ tion estimate of the location hypothesis.
- adjusting uses archival information related to the accuracy and/or reliability of previously generated location hypotheses;
- the location estimate is provided in a data structure (or object class) denoted as a "lo ⁇ tion hypothesis" (illustrated in Table LH-i). Brief descriptions of the da ⁇ fields for a lo ⁇ tion hypothesis is provided in the Table LH-i.
- each lo ⁇ tion hypothesis data structure includes at least one measurement, denoted hereinafter as a confidence value (or simply confidence), that is a measurement of the perceived likelihood that an MS lo ⁇ tion estimate in the location hypothesis is an accurate location estimate of the target MS 140. Since, in some embodiments of the invention, such confidence values are an important aspect, much of the description and use of such confidence values are described below; however, a brief description is provided here.
- each confidence value is a probability indicative of a likeliness that the target MS 140 resides within an geographic area represented by the hypothesis to which the confidence value applies. Accordingly, each such confidence value is in the range [0, 1]. Moreover, for clarity of discussion, it is assumed that unless stated otherwise that the probabilistic definition provided here is to be used when confidence values are discussed.
- confidence values are within the scope of the present invention that may be more general than probabilities, and/or that have different ranges other than [0, ij.
- each such confidence value is in the range -1.0 to i.o, wherein the larger the value, the greater the perceived likelihood that the target MS 140 is in (or at) a corresponding MS location estimate of the location hypothesis to which the confidence value applies.
- a location hypothesis may have more than one MS location estimate (as will be discussed in detail below) and the confidence value will typically only correspond or apply to one of the MS location estimates in the location hypothesis.
- values for the confidence value field may be interpreted as: (a) -1.0 means that the target MS 140 is NOT in such a corresponding MS area estimate of the location hypothesis area, (b) 0 means that it is unknown as to the likelihood of whether the MS 140 in the corresponding MS area estimate, and (c) +1.0 means that the MS 140 is perceived to positively be in the corresponding MS area estimate.
- a confidence score, CS A can be assigned to A, wherein the confidence score for such an area is a function of the confidences for all the lo ⁇ tion hypotheses whose (most pertinent) target MS location estimates contain A. That is, in order to determine a most likely target MS location area estimate for outputting from the lo ⁇ tion center/gateway 142, a confidence score is determined for areas within the location center/gateway service area.
- area type as related to wireless signal transmission characteristics has been used in many investigations of radio signal transmission characteristics. Some investigators, when investigating such signal characteristics of areas have used somewhat naive area classifications such as urban, suburban, rural, m. However, it is desirable for the purposes of the present invention to have a more operational definition of area types that is more closely associated with wireless signal transmission behaviors.
- wireless communication components or infrastructure in the area e.g., the arrangement and signal communication characteristics of the base stations 122 in the area (e.g., base station antenna dow ⁇ tilt). Further, the antenna characteristics at the base stations 122 may be important criteria.
- a description of wireless signal characteristics for determining area types could potentially include a characterization of wireless signaling attributes as they relate to each of the above criteria.
- an area type might be: hilly, treed, suburban, having no buildings above 50 fta, with base stations spaced apart by two miles.
- a ⁇ tegorization of area types is desired that is both more closely tied to the wireless signaling characteristics of the area, and is capable of being computed substantially automatically and repeatedly over time.
- the primary wireless signaling characteristics for categorizing areas into at least minimally similar area types are: thermal noise and, more importantly, multipath characteristics (e.g., multipath fade and time delay).
- transmission area type or, "area type” when both a generic area type classifi ⁇ tion scheme and the transmission area type discussed hereinafter are intended
- transmission area type or, "area type” when both a generic area type classifi ⁇ tion scheme and the transmission area type discussed hereinafter are intended
- the novel transmission area type scheme of the present invention is based on: (a) the terrain area classifications; e.g., the terrain of an area surrounding a target MS 140, (b) the configuration of base stations 122 in the radio coverage area 120, and (c) characterizations of the wireless signal transmission paths between a target MS 140 location and the base stations 122.
- a partition (denoted hereinafter as PJ is imposed upon the radio coverage area 120 for partitioning for radio coverage area into subareas, wherein each subarea is an estimate of an area having included MS 140 lorations that are likely to have is at least a minimal amount of similarity in their wireless signaling characteristics.
- a first such collection may be (for the forward transmission path) the active set of base stations 122, or, the union of the active and candidate sets, or, the union of the active, candidate and/or remaining sets of base stations 122 detected by "most" MSs 140 in .
- a second such collection may be the base stations 12 that are expected to detect MSs 140 at locations within the subarea.
- the union or intersection of the first and second collections is also within the scope of the present invention for partitioning the radio coverage area 120 according to (d) above. It is worth noting that it is believed that base station 122 power levels will be substantially constant.
- one or more collections for (d) above may be determined empirically and/or by computationally simulating the power output of each base station 122 at a predetermined level.
- this step is relatively straightforward to implement using the data stored in the lo ⁇ tion signature data base 1320 (i.e., the verified location signature clusters discussed in detail hereinbelow). Denote the resulting partition here as P,.
- a subarea, A, of P 1? may be ⁇ tegorized or labeled according to the number of base stations 122 in each of the collections used in
- each category may correspond to a single number x (such as 3), wherein for a subarea, A, of this category, there is a group of x (e.g., three) base stations 122 that are expected to be detected by a most target MSs 140 in the area A.
- each category may correspond to a triple: of numbers such as (5, 2, i), wherein for a subarea A of this category, there is a common group of 5 base stations 122 with two-way signal detection expected with most locations (e.g., within a first or second deviation) within A, there are 2 base stations that are expected to be detected by a target MS 140 in A but these base stations can not detectthe target MS, and there is one base station 122 that is expected to be able to detect a target MS in A but not be detected. (23.8.4.5) Determine an area type categorization scheme for the subareas of P 2 . Note that the subareas of P 2 may be categorized according to their similarities.
- such categories may be somewhat similar to the naive area types mentioned above (e.g., dense urban, urban, suburban, rural, mountain, etc.). However, it is also an aspect of the present invention that more precise categorizations may be used, such as a category for all areas having between 20,000 and 30,000 square feet of vertical area change per 11,000 square feet of horizontal area and also having a high traffic volume (such a category likely corresponding to a "moderately dense urban" area type).
- one such approximation is a straight line between C(A) and each of the base stations 122 in the group.
- other such approximations are within the scope of the present invention, such as, a generally triangular shaped area as the transmission path, wherein a first vertex of this area is at the corresponding base s ⁇ tion for the transmission path, and the sides of the generally triangular shaped defining the first vertex have a smallest angle between them that allows A to be completely between these sides.
- any other P 0 subarea having the same (or substantially similar) collection of lists of P 0 area types will be viewed as having approximately the same radio transmission characteristics.
- transmission signal characteristics may be incorporated into the transmission area types.
- thermal noise characteristics may be included by providing a third radio coverage area 120 partition, P,, in addition to the partitions of P, and P 2 generated in (23.8.4.1) and (23.8.4.2) respectively.
- the time varying characteristics of (23.8.2) may be incorporated in the transmission area type frame work by generating multiple versions of the transmission area types such that the transmission area type for a given subarea of P 0 may change depending on the combination of time varying environmental characteristics to be considered in the transmission area types. For instance, to account for seasonality, four versions of the partitions P, and P 2 may be generated, one for each of the seasons, and subsequently generate a (potentially) different partition P 0 for each season. Further, the type and/or charatteristics of base station 122 antennas may also be included in an embodiment of the transmission area type.
- each of the first order models 1224 have default confidence values associated therewith, and these confidence values may be probabilities. More precisely, such probability confidence values an be determined as follows. Assume there is a partition of the coverage area into subareas, each subarea being denoted a "partition area.” For each partition area, activate each first order model 1224 with histori ⁇ l location data in the Location Signature Data Base 1320 (Fig.6), wherein the histori ⁇ l location data has been obtained from corresponding known mobile station lo ⁇ tions in the partition area. For each first order model, determine a probability of the first order model generating a location hypothesis whose location estimate contains the corresponding known mobile station location.
- each partition area A is specified as the collection of coverage area locations such that for each location, the detetted wireless transmissions between the network base stations and a target mobile station at the location can be straightforwardly equated with other locations of area A.
- each partition area A is specified in terms of three sets of base station identifiers, namely, (a) the base station identifiers of the base stations that can be detected at each location of A and can detect a target mobile station at each location, (b) the identifiers for base stations that can detect a target mobile station at each location of A, but can not be detected by the target mobile station, and (c) the identifiers for base stations that can be detected by a target mobile station at each location of A, but these base stations n not detect the target mobile station. That is, two lo ⁇ tions, I, and ⁇ . are identified as being in A if and only if the three sets of (a), (b), and (c) for I, are, respectively, identical to the three sets of(a),(b),and(c)forl,
- a description can be given as to how probabilities may be assigned as the confidence values of location hypotheses generated by the first order models 1224.
- a first order model 1224 is supplied with wireless measurements of archived lo ⁇ tion data in the Lo ⁇ tion Signature Data Base associated with corresponding verified mobile station locations.
- a probability can be determined as to how likely the first order model is to generate a lo ⁇ tion hypothesis having a location estimate containing the corresponding verified mobile station location.
- a table of partition area probabilities can be determined for each fi ⁇ t order model 1224.
- the corresponding probability for that partition area may be assigned as the confidence value for the location hypothesis.
- the most likelihood estimator 1344 can compute a straightforward probability for each distinct intersection of the multiple lo ⁇ tion hypotheses generated by the multiple first order models, such that each such probability indicates a likelihood thatthe target mobile station is in the corresponding intersection.
- MS lo ⁇ tion processing performed by the lo ⁇ tion center/gateway 142 should become increasingly better at locating a target MS 140 both by (a) building an increasingly more detailed model of the signal characteristics of lo ⁇ tions in the service area for the present invention, and also (b) by providing capabilities for the lo ⁇ tion center processing to adapt to environmental changes.
- One way these aspects of the present invention are realized is by providing one or more data base management systems and data bases for: (a) storing and associating wireless MS signal charatteristics with known lo ⁇ tions of MSs 140 used in providing the signal charatteristics.
- Such stored associations may not only provide an increasingly better model of the signal characteristics of the geography of the service area, but also provide an increasingly better model of more changeable signal characteristic affecting environmental factors such as weather, seasons, and/or traffic patterns; (b) adaptively updating the signal characteristic data stored so that it reflects changes in the environment of the service area such as, for example, a new high rise building or a new highway.
- lo ⁇ tion information data bases 1232 include a data base for providing training and/or calibration data to one or more trainable/ ⁇ libratable FOMs 1224, as well as an archival data base for archiving historical MS lo ⁇ tion information related to the performance of the FOMs.
- data bases will be discussed as necessary hereinbelow.
- archival data base is provided here. Accordingly, the term, "lo ⁇ tion signature data base" is used hereinafter to denote the archival data base and/or data base management system depending on the context of the discussion.
- the lo ⁇ tion signature data base (shown in, for example, Fig.6 and labeled 1320) is a repository for wireless signal characteristic data derived from wireless signal communi ⁇ tions between an MS 140 and one or more base stations 122, wherein the corresponding lo ⁇ tion of the MS 140 is known and also stored in the location signature data base 1320. More particularly, the location signature data base 1320 associates each such known MS lo ⁇ tion with the wireless signal charatteristic data derived from wireless signal communi ⁇ tions between the MS 140 and one or more base stations 122 at this MS lo ⁇ tion. Accordingly, it is an aspect of the present invention to utilize such historical MS signal lo ⁇ tion data for enhancing the correctness and/or confidence of certain lo ⁇ tion hypotheses as will be described in detail in other sections below.
- lo ⁇ tion signature data base 1320 there are four fundamental entity types (or object classes in an object oriented programming paradigm) utilized in the lo ⁇ tion signature data base 1320. Briefly, these data entities are described in the items (24.1) through (24.4) thatfollow:
- each such (verified) lo ⁇ tion signature describes the wireless signal characteristic measurements between a given base station (e.g., BS 122 or LBS 152) and an MS 140 at a (verified or known) lo ⁇ tion associated with the (verified) lo ⁇ tion signature. That is, a verified lo ⁇ tion signature corresponds to a lo ⁇ tion whose coordinates such as latitude-longitude coordinates are known, while simply a lo ⁇ tion signature may have a known or unknown lo ⁇ tion corresponding with it.
- the term (verified) lo ⁇ tion signature is also denoted by the abbreviation, "(verified) loc sig" hereinbelow;
- Each such (verified) lo ⁇ tion signature cluster includes a collection of (verified) lo ⁇ tion signatures corresponding to all the lo ⁇ tion signatures between a target MS 140 at a (possibly verified) presumed substantially stationary lo ⁇ tion and each BS (e.g., 122 or 152) from which the target MS 140 an detect the BS's pilot channel regardless of the classification of the BS in the target MS (i.e, for CDMA, regardless of whether a BS is in the MS's active, ⁇ ndidate or remaining base station sets, as one skilled in the art will understand).
- each BS e.g., 122 or 152
- each location signature cluster has a single fixed primary base station to which the target MS 140 synchronizes or obtains its timing; (24.3) "composite location objects (or entities)": Each such entity is a more general entity than the verified location signature cluster.
- An object of this type is a collection of (verified) lo ⁇ tion signatures that are associated with the same MS 140 at substantially the same location at the same time and each such loc sig is associated with a different base station.
- a loc sig is, in one embodiment, an instance of the data structure containing the signal characteristic measurements output by the signal filtering and normalizing subsystem also denoted as the signal processing subsystem 1220 describing the signals between: (i) a specific base station 122 (BS) and (ii) a mobile station 140 (MS), wherein the BS's location is known and the MS's location is assumed to be substantially constant (during a 2-5 second interval in one embodiment of the present invention), during communi ⁇ tion with the MS 140 for obtaining a single instance of loc sig da ⁇ , although the MS location may or may not be known.
- BS specific base station 122
- MS mobile station 140
- the BS 122 and the MS 140 for a loc sig hereinafter will be denoted the "BS associated with the loc sig", and the “MS associated with the loc sig” respectively.
- the location of the MS 140 at the time the loc sig data is obtained will be denoted the "location associated with the loc sig” (this location possibly being unknown).
- Fig.5 presents a high level diagram of an embodiment of the lo ⁇ tion center/gateway 142 and the lo ⁇ tion engine 139 in the context of the infrastructure for the entire lo ⁇ tion system of the present invention.
- the architecture for the lo ⁇ tion center/gateway 142 and the lo ⁇ tion engine 139 provided by the present invention is designed for extensibility and flexibility so that MS 140 lo ⁇ tion accuracy and reliability may be enhanced as further location data become available and as enhanced MS lo ⁇ tion techniques become available.
- the high level architecture for generating and processing MS lo ⁇ tion estimates may be considered as divided into the following high level functional groups described hereinbelow.
- a first functional group of lo ⁇ tion engine 139 modules is for performing signal processing and filtering of MS location signal data received from a conventional wireless (e.g., (DMA) infrastructure, as discussed in the steps (23.1) and (23.2) above.
- This group is denoted the signal processing subsystem 1220 herein.
- One embodiment of such a subsystem is described in the U.S. copending patent application titled, "Wireless Lo ⁇ tion Using A Plurality of (o shockal Network Infrastructures," by F. W. LeBlanc, Dupray and Karr filed Jan.22, 1999 and having U.S. Patent No.6,236365. Note that this copending patent appli ⁇ tion is incorporated herein entirely by reference since it may contain essential material for the present invention..
- the signal processing subsystem 20 may be unnecessary for the gateway 142 unless the gateway supplies wireless location signal data to one or more FOMs.
- a second functional group of modules at least accessible by the lo ⁇ tion engine 139 are the FOM 1224 for generating various tar ⁇ tt MS 140 lo ⁇ tion initial estimates, as described in step (23.3).
- Fig.8 illustrates another, more detail view of an embodiment of the lo ⁇ tion center/gateway 142 for the present invention.
- this figure illustrates some of the FOMs 1224 at least accessible (but not necessarily co-located with the other lo ⁇ tion center/gateway modules shown in this figure), and additionally illustrates the primary communi ⁇ tions with other modules of the gateway.
- the present invention is not limited to the FOMs 1224 shown and discussed herein.
- each FOM type may have a plurality of its MS location estimating models (at least) accessible by the gateway 142.
- TCSO 1224 models of this type are referred to as “terrestrial communi ⁇ tion station ofiset (TCSO) models” or “terrestrial communi ⁇ tion station offset (TOO) first order models", or “terrestrial communi ⁇ tion station offset (TCSO) FOMs"
- TCSO terrestrial communi ⁇ tion station ofiset
- TOO terrestrial communi ⁇ tion station offset
- TCSO FOMs may be based on a range, offset, and/or distance computation such as on a base station signal reception angle determination between the target MS 140 from each of one or more base stations.
- such TCSO models 1224 determine a lo ⁇ tion estimate of the target MS 140 by determining an offset from each of one or more base stations 122, possibly in a particular direction from each (some of) the base stations, so that, e.g., an intersection of each area locus defined by the base station offsets may provide an estimate of the lo ⁇ tion of the target MS.
- TCSO FOMs 1224 may compute such offsets based on, e.g.: (a) signal timing measurements between the target mobile station 140 and one or more base stations 122; e.g.., timing measurements such as time difference of arrival (TDOA), or time of arrival (TOA).
- TDOA time difference of arrival
- TOA time of arrival
- both forward and reverse signal path timing measurements may be utilized; (b) signal strength measurements (e.g., relative to power control settings of the MS 140 and/or one or more BS 122); and/or (c) signal angle of arrival measurements, or ranges thereof, atone or more base stations 122 (such angles and/or angular ranges provided by, e.g., base station antenna sectors having angular ranges of 120 0 or 6o°, or, so called "SMART antennas" with variable angular transmission ranges of2° to 120°).
- a terrestrial communication station offset (TCSO) model may utilize, e.g., triangulation or trilateration to compute a location hypothesis having either an area lo ⁇ tion or a point lo ⁇ tion for an estimate of the target MS 140. Additionally, in some embodiments location hypothesis may include an estimated error.
- TCSO terrestrial communication station offset
- FOM 1224 is a statistically based first order model 1224, wherein a statistical technique, such as regression techniques (e.g., least squares, partial leastsquares, principle decomposition), or e.g., Bollenger Bands (e.g., for computing minimum and maximum base station offsets).
- models of this type output lo ⁇ tion hypotheses determined by performing one or more statistical techniques or comparisons between the verified location signatures in location signature data base 1320, and the wireless signal measurements from a target MS.
- Models of this type are also referred to hereinafter as a “stochastic signal (firstorder) model” or a “stochastic FOM” or a “statistical model.”
- statistically based FOMs may be a hybrid combination with another type of FOM such as a TCSO FOM.
- Still another type of FOM 1224 is an adaptive learning model, such as an artificial neural net or a genetic algorithm, wherein the FOM may be trained to recognize or associate each of a plurality of lo ⁇ tions with a corresponding set of signal characteristics for communi ⁇ tions between the ⁇ rget MS 140 (at the lo ⁇ tion) and the base stations 122. Moreover, typi ⁇ lly such a FOM is expected to accurately interpolate/extrapolate target MS 140 lo ⁇ tion estimates from a set of signal characteristics from an unknown target MS 140 location. Models of this type are also referred to hereinafter variously as “artificial neural net models” or “neural net models” or “trainable models” or “learning models.” Note that a related type of FOM 1224 is based on pattern recognition.
- FOMs n recognize patterns in the signal characteristics of communi ⁇ tions between the target MS 140 (at the lo ⁇ tion) and the base stations 122 and thereby estimate a location area of the target MS.
- FOMs may not be trainable.
- Yet another type of FOM 1224 can be based on a collection of dispersed low power, low cost fixed location wireless transceivers (also denoted
- lo ⁇ tion base stations 152 hereinabove
- a target MS 140 in areas where, e.g., there is insufficient base station 122 infrastructure coverage for providing a desired level of MS 140 lo ⁇ tion accuracy.
- lo ⁇ tion base stations 152 can be directed to activate and deactivate via the direction of a FOM 1224 of the present type, then these lo ⁇ tion base stations ⁇ be used to both location a target MS 140 and also provide indi ⁇ tions of where the target MS is not.
- lo ⁇ tion base stations 152 populating an area where the target MS 140 is presumed to be
- evidence may be obtained as to whether or not the target MS is actually in the area; e.g., if the target MS 140 is detected by a location base station 152, then a corresponding lo ⁇ tion hypothesis having a lo ⁇ tion estimate corresponding to the coverage area of the location base station may have a very high confidence value.
- a corresponding location hypothesis having a lo ⁇ tion estimate corresponding to the coverage area of the location base station may have a very low confidence value.
- Models of this type are referred to hereinafter as "lo ⁇ tion base station models.”
- Yet another type of FOM 1224 can be based on input from a mobile base station 148, wherein lo ⁇ tion hypotheses may be generated from target MS 140 lo ⁇ tion data received from the mobile base station 148.
- FOM 1224 an be based on various techniques for recognizing wireless signal measurement patterns and associating particular patterns with locations in the coverage area 120. For example, artificial neural networks or other learning models an used as the basis for various FOMs.
- the substantially simultaneous use or activation of a potentially large number of such first order models 1224 may be able to enhance both the reliability of location estimates and the accuracy of such estimates.
- the first order models 1224 an be activated when appropriate signal measurements are obtained. For example, a TDOA FOM may be activated when only a single signal time delay measurement is obtained from some plurality of base station 122.
- one or more wireless signal pattern matching FOM may also be activated in conjunction with the TDOA FOM.
- a FOM using satellite signals e.g., GPS
- satellite signals e.g., GPS
- output from such a FOM may dominate any other previous or simultaneous estimates unless there is evidence to the contrary.
- the present invention provides a framework for incorporating MS location estimators to be subsequently provided as new FOMs in a straightforward manner.
- a FOM 1224 based on wireless signal time delay measurements from a distributed antenna system for wireless communi ⁇ tion may be incorporated into the present invention for thereby locating a target MS 140 in an enclosed area serviced by the distributed antenna system.
- the present invention may determine the floor of a multi-story building from which a target MS is transmitting.
- MSs 140 n be ioated in three dimensions using such a distributed antenna FOM.
- FOMs for detecting certain registration changes within, for example, a public switched telephone network an also be used for lo ⁇ ting a target MS 140.
- the device may be an associated or dedi ⁇ ted device for each such MS that allows the MS to function as a cordless phone to a line based telephone network when the device detects thatthe MS is within signaling range.
- the device registers with a home location register of the public switched telephone network when there is a status change such as from not detecting the corresponding MS to detecting the MS, or visa vena, as one skilled in the art will unders ⁇ nd.
- the lo ⁇ tion engine 139 can determine whether the MS is within signaling range of the home base station or not, and generate location hypotheses accordingly.
- FOMs based on, for example, chaos theory and/or fractal theory are also possible.
- Each such fint order model 1224 may be relatively easily incorporated into and/or removed from the present invention.
- the signal processing subsystem 1220 provides uniform input to the FOMs, and there is a uniform FOM output interface (e.g., API), it is believed that a large majority (if not substantially all) viable MS location estimation strategies may be accommodated.
- FOMs 1224 (28.2)
- first order models 1224 may be relatively simple and still provide significant MS 140 locating functionality and predictability.
- the present invention is modular and extensible such that, for example, (and importantly) different first order models 1224 may be utilized depending on the signal transmission characteristics of the geographic region serviced by an embodiment of the present invention.
- a simple configuration of the present invention may have (or access) a small number of FOMs 1224 for a simple wireless signal environment (e.g., flat terrain, no urban canyons and low population density).
- a large number of FOMs 1224 may be simultaneously utilized for generating MS location b ⁇ thm.
- a third functional group of location engine 139 modules evaluates lo ⁇ tion hypotheses output by the first order models 1224 and thereby provides a "most likely" target MS lo ⁇ tion estimate.
- the modules for this functional group are collectively denoted the hypothesis evaluator 1228.
- Hypothesis Evaluator A primary pupe oftJie hypothesis evaluatori228 is to mitigate conflicts and ambiguities related to location hypotheses output by the fi ⁇ t order models 1224 and thereby output a "most likely" estimate of an MS for which there is a request for it to be located.
- each lo ⁇ tion hypothesis includes both an MS lo ⁇ tion area estimate and a corresponding confidence value indicating a perceived confidence or likelihood of the target MS being within the corresponding lo ⁇ tion area estimate, there is a monotonic relationship between MS location area estimates and confidence values.
- the corresponding confidence value may also be increased (in an extreme case, the lo ⁇ tion area estimate could be the entire coverage area 120 and thus the confidence value may likely correspond to the highest level of certainty; i.e., +1.0). Accordingly, given a target MS lo ⁇ tion area estimate (of a location hypothesis), an adjustment to its accuracy may be performed by adjusting the MS lo ⁇ tion area estimate and/or the corresponding confidence value. Thus, if the confidence value is, for example, excessively low then the area estimate may be increased as a technique for increasing the confidence value. Alternatively, if the estimated area is excessively large, and there is flexibility in the corresponding confidence value, then the estimated area may be decreased and the confidence value also decreased.
- the lo ⁇ tion hypothec ' s is judged to be more (less) accurate than initially determined, then (i) the confidence value of the lo ⁇ tion hypothesis may be increased (decreased), and/or (ii) the MS location area estimate an be decreased (increased).
- the confidence values are probabilities, such adjustments are may require the reactivation of one or more FOMs 1224 with requests to generate lo ⁇ tion hypotheses having location estimates of differentsizes.
- adjuster modules 1436 and/on ⁇ o may be invoked for generating location hypotheses havingarea estimates of differentsizes.
- the confidence value on such an adjusted location hypothesis may also be a probability in that combinations of FOMs 1224 and adjuster modules 1436 and 1440 can also be calibrated for thereby yielding probabilities as confidence values to the resulting location hypotheses.
- the hypothesis evaluator 1228 evaluates loration hypotheses and adjusts or modifies only their confidence values for MS lo ⁇ tion area estimates and subsequently uses these MS lo ⁇ tion estimates with the adjusted confidence values for determining a "most likely" MS location estimate for outputting.
- MS lo ⁇ tion area estimates an be adjusted while confidence values remain substantially fixed.
- both location hypothesis area estimates and confidence values are modified.
- the hypothesis evaluator 1228 may perform any or most of the following tasks depending on the embodiment of the hypothesis evaluator.
- the initial location hypothesis may enhance the accuracy of an initial location hypothesis generated by an FOM by using the initial location hypothesis as, essentially, a query or index into the location signature data base 1320 for obtaining one or more corresponding enhanced location hypotheses, wherein the enhanced location hypotheses have both an adjusted target MS location area estimates and an adjusted confidences based on past performance of the FOM in the location service surrounding the target MS location estimate of the initial lo ⁇ tion hypothesis;
- the hypothesis evaluator 1228 may utilize environmental information to improve and reconcile lo ⁇ tion hypotheses supplied by the fi ⁇ t order models 1224.
- a basic premise in this context is that the accuracy of the individual fi ⁇ t order models may be affected by various environmental factors such as, for example, the season of the year, the time of day, the weather conditions, the presence of buildings, base station failures, etc; (303) the hypothesis evaluator 1228 may determine how well the associated signal characteristics used for locating a target MS compare with particular verified loc sigs stored in the lo ⁇ tion signature data base 1320 (see the lo ⁇ tion signature data base section for further discussion regarding this aspett of the invention).
- verified loc sigs (which were previously obtained from one or more verified lo ⁇ tions of one or more MS's) are retrieved for an area corresponding to the lo ⁇ tion area estimate of the loration hypothesis, and the signal characteristics of these verified loc sigs are compared with the signal charatteristics used to generate the location hypothesis for determining their similarities and subsequently an adjustment to the confidence of the loration hypothesis (and/or the size of the loration area estimate); (30.4) the hypothesis evaluatori228 may determine if (or howwell) such lo ⁇ tion hypotheses are consistent with well known physical constraints such as the laws of physics. For example, if the difference between a previous (most likely) loration estimate of a target MS and a loration estimate by a current lo ⁇ tion hypothesis requires the MS to:
- the confidence in the current lo ⁇ tion hypothesis may be increased.
- the hypothesis eva!uatori228 may determine consistencies and inconsistencies between location hypotheses obtained from differentfirstorder models. For example, if two such location hypotheses, for substantially the same timestamp, have estimated lo ⁇ tion areas where the target
- the confidence in both such location hypotheses may be increased.
- a velocity of an MS may be determined (via deltas of successive lo ⁇ tion hypotheses from one or more fi ⁇ t order models) even when there is low confidence in the lo ⁇ tion estimates forthe MS, since such deltas may, in some ⁇ ses, be more reliable than the actual target MS loration estimates; (30.6) the hypothesis evaluator 1228 determines new (more accurate) loration hypotheses from other loration hypotheses. For example, this module may generate new hypotheses from currently active ones by decomposing a location hypothesis having a ⁇ rgetMS location estimate intersecting two radially different wireless signaling area types.
- this module may generate lo ⁇ tion hypotheses indicating areas of poor reception; and (30.7) the hypothesis evaluator 1228 determines and outputs a most likely location hypothesis for a target MS.
- additional description of the hypothesis evaluator 1228 can be found in one of the following two copending U.S. patent applications which are incorporated herein by reference: (a) "Location Of A Mobile Station” filed Nov.24, 1999 having Application No. 09/194367 whose inventors are D. J. Dupray and C. L Karr, and (b) "A Wireless Location System For Calibrating Multiple Lo ⁇ tion Estimators" filed October 21, 1998 having Application No. oq/176,587 whose inventor is ⁇ . J. Dupray, wherein these copending patent applications may have essential material for the present specification. In particular, these copending patent applications may have essential material relating to their descriptions of the hypothesis evaluator.
- the context adjuster 1326 module enhances both the comparability and predictability of the location hypotheses output by the first order models 1224.
- this module modifies lo ⁇ tion hypotheses received from the FOMs 1224 so that the resulting loration hypotheses output by the context adjuster 1326 may be further processed uniformly and substantially without concern as to differences in accuracy between the fi ⁇ t order models from which loration hypotheses originate.
- embodiments of the context adjuster may determine those fatten that are perceived to impart the perceived accuracy (e.g., confidence) of the location hypotheses:.
- environmental characteristics may be ⁇ ken into account here, such as time of day, season, month, weather, geographical area categorizations (e.g., dense urban, urban, suburban, rural, mountain, etc.), area sub ⁇ tegorizations (e.g., heavily treed, hilly, high traffic area, etc.).
- geographical area categorizations e.g., dense urban, urban, suburban, rural, mountain, etc.
- area sub ⁇ tegorizations e.g., heavily treed, hilly, high traffic area, etc.
- Fig.16 two such adjuster modules are shown, namely, an adjuster for enhancing reliability 1436 and an adjuster for enhancing accuracy 1440. Both of these adjuste ⁇ perform their location hypothesis adjustments in the manner described above. The difference between these two adjuster modules 1436 and 1440 is primarily the size of the localized area "nearby" the newly generated location estimate.
- the adjuster for enhancing reliability 1436 may determine its localized areas "nearby" a newly generated lo ⁇ tion estimate as, for example, having a 40% larger diameter (alternatively, area) than the lo ⁇ tion area estimate generated by a first order model 1224.
- the adjuster for enhancing accuracy 1444 may determine its localized areas "nearby” a newly generated location estimate as, for example, having a 30% smaller diameter (alternatively, area) than the location area estimate generated by a first order model 1224.
- each newly generated lo ⁇ tion hypothesis an potentially be used to derive at least two additional adjusted location hypotheses with some of these adjusted location hypotheses being more reliable and some being more accurate than the location hypotheses generated directly from the first order models 1224.
- additional description of context adjuster aspects of the present invention can be found in the following two copending U.S. patent applications which are incorporated herein by reference: (a) "Location Of A Mobile Station” filed Nov.24, 1999 having Application No. 09/194367 whose inventors are D. J. Dupray and C. L. Karr, and (b) "A Wireless Location System For Calibrating Multiple Location Estimators" filed October 21, 1998 having Application No.09/176,587 whose inventor is D. J. Dupray, wherein these copending patent applications may have essential material for the present specification. In particular, these copending patent applications may have essential material relating to the context adjuster 1326.
- the MS status repository 1338 is a run-time storage manager for storing lo ⁇ tion hypotheses from previous activations of the location engine 139 (as well as for storing the output "most likely" target MS location estimated) so that a target MS 140 may be tracked using ⁇ rget MS lo ⁇ tion hypotheses from previous lo ⁇ tion engine 139 activations to determine, for example, a movement of the target MS 140 between evaluations of the target MS lo ⁇ tion.
- the location hypothesis analyzer may adjust confidence values of the location hypotheses, according to: (a) heuristics and/or statistical methods related to how well the signal characteristics for the generated target MS location hypothesis matches with previously obtained signal characteristics for verified MS locations. (b) heuristics related to how consistent the lo ⁇ tion hypothesis is with physi ⁇ l laws, and/or highly probable reasonableness conditions relating to the lo ⁇ tion of the target MS and its movement characteristics. For example, such heuristics may utilize knowledge of the geographi ⁇ l terrain in which the MS is estimated to be, and/or, for instance, the MS velocity, acceleration or extrapolation of an MS position, velocity, or acceleration.
- the most likelihood estimator 1344 is a module for determining a "most likely" location estimate for a target MS being lo ⁇ ted by the location engine 139.
- the most likelihood estimator 1344 receives a collection of active or relevant lo ⁇ tion hypotheses from the hypothesis analyzer 1332 and uses these location hypotheses to determine one or more most likely estimates for the target MS 140.
- an area of interest is fi ⁇ t determined which contains the target MS 140 whose location is desired. This ran be straightforwardly determined by identifying the base stations 122 that can be detected by the ⁇ rget MS 140 and/or the base stations 140 that can detect the target MS.
- this area of interest has been previously partitioned into "cells" (eg., small rectangular areas of, for example, 50 to 200 feet per side) and that the resulting location hypotheses for estimating the lo ⁇ tion of the target MS 140 each have a likelihood probability associated therewith
- a probability (more generally confidence value) is ⁇ pable of being assigned to each cell intersecting and/or included in the associated target MS location estimate.
- a portion of the probability value, P, for the associated location estimate, A ran be assigned to each cell, C, intersecting the estimate.
- One simple way to perform this is to divide P by the number of cells C, and increment, for each cell C, a corresponding probability indicative of the target MS 140 being in C with the resultfrom the division.
- incrementing such cell probabilities including: providing a Gaussian or other probabilistic distribution of probability values according to, e.g., the distance of the cell from the centroid of the lo ⁇ tion estimate. Accordingly, assuming all such probability increments have been assigned to all such cells C from al! lo ⁇ tion hypotheses generated for lorating the target MS 140, then the following is one embodiment of a program for determining one or more most likely lo ⁇ tions of the target MS. Desired el r getthe desired reliability for the resulting lo ⁇ tion estimate; Maxjize r getthe desired maximum extent forthe resulting lo ⁇ tion estimate;
- Result instead of "building" Result as provided in the above program, Result an be "whittled” from the area of interest. Accordingly, Result would be initialized to the entire area of interest, and cells would be selected for removal from Result. Additionally, note that the above program determines a fast approximation to the optimal most likely area containing the target MS 140 having at least a particular desired confidence.
- the hypothesis evaluator 1228 it is important to note that not all the above mentioned modules are required in all embodiments of the present invention. In particular, the hypothesis analyzer 1332 may be unnecessary. Accordingly, in such an embodiment, the enhanced lo ⁇ tion hypotheses output by the context adjuster 1326 are provided directly to the most likelihood estimator 1344.
- a fourth functional group of location engine 139 modules is the control and output gating modules which includes the lo ⁇ tion center control subsystem 1350, and the output gateway 1356.
- the location control subsystem 1350 provides the highest level of control and monitoring of the data processing performed by the lo ⁇ tion center 142. In particular, this subsystem performs the following functions:
- this subsystem may receive (via, e.g., the public telephone switching network and Internet 468) such environmental information as increased signal noise in a particular service area due to increase traffic, a change in weather conditions, a base station 122 (or other infrastructure provisioning), change in operation status
- this subsystem may receive (via, e.g., the public telephone switching network and Internet 468) such environmental information as increased signal noise in a particular service area due to increase traffic, a change in weather conditions, a base station 122 (or other infrastructure provisioning), change in operation status
- (c) receives and directs lo ⁇ tion processing requests from other lo ⁇ tion centers 142 (via, e.g., the Internet);
- (d) performs accounting and billing procedures such as billing according to MS location accuracy and the frequency with which an MS is located; (e) interacts with location center operators by, for example, receiving operator commands and providing output indicative of processing resources being utilized and malfunctions; (f) provides access to output requirements for various applications requesting location estimates. For example, an Internet location request from a trucking company in Los Angeles to a location center 142 in Denver may only want to know if a particular truck or driver is within the Denver area. Alternatively, a local medial rescue unit is likely to request a precise a lo ⁇ tion estimate as possible. Note that in Fig.6, (a) - (d) above are, at least at a high level, performed by utilizing the operator interface 1374.
- this module routes target MS 140 loration estimates to the appropriate loration applications). For instance, upon receiving a location estimate from the most likelihood estimator 1344, the output gateway 1356 may determine thatthe loration estimate is for an automobile being tracked by the police and therefore must be provided must be provided according to the particular protocol.
- System Tuning and Adaptation The Adaptation Engine
- a fifth functional group of location engine 139 modules provides the ability to enhance the MS locating reliability and/or accuracy of the present invention by providing it with the capability to adapt to particular operating configurations, operating conditions and wireless signaling environments without performing intensive manual analysis of the performance of various embodiments of the location engine 139. That is, this functional group automatically enhances the performance of the lo ⁇ tion engine for locating MSs 140 within a particular coverage area 120 using at least one wireless network infrastructure therein. More precisely, this functional group allows the present invention to adapt by tuning or optimizing certain system paramete ⁇ according to lo ⁇ tion engine 139 location estimate accuracy and reliability.
- the present invention may include a module, denoted herein as an "adaptation engine” 1382, that performs an optimization procedure on the lo ⁇ tion center ⁇ system paramete ⁇ either periodically or concurrently with the operation of the lo ⁇ tion center in estimating MS lo ⁇ tions. That is, the adaptation engine 1382 directs the modifications of the system paramete ⁇ so that the lo ⁇ tion engine 139 increases in overall accuracy in locating target MSs 140.
- the adaptation engine 1382 includes an embodiment of a genetic algorithm as the mechanism for modifying the system paramete ⁇ . Genetic algorithms are basically search algorithms based on the mechanics of natural genetics.
- first order models 1224 are provided in this section. However, it is important to note that these are merely representative embodiments of location estimators that are within the scope of the present invention.
- two or more of the wireless location technologies described hereinbelow may be combined to created additional First Order Models.
- various triangulation techniques between a target MS 140 and the base station infrastructure e.g., time difference of arrival (TDOA) or time of arrival (TOA)
- TDOA time difference of arrival
- TOA time of arrival
- AOA angle of arrival
- TCSO Terrestrial Communication Station Offset
- TOA/TDOA/AOA TOA/TDOA/AOA
- TCSO models determine a presumed direction and/or distance (more generally, an offset) that a target MS 140 is from one or more base stations 122.
- the target MS lo ⁇ tion estimated) generated are obtained using radio signal analysis techniques that are quite general and therefore are not capable of taking into account the peculiarities of the topography of a particular radio coverage area.
- substantially all radio signal analysis techniques using conventional procedures (or formulas) are based on "signal characteristic measurements" such as: (a) signal timing measurements (e.g., TOA and TDOA), and/or (b) signal strength measurements.
- each base station (BS) 122 is required to emit a cons ⁇ nt signal-strength pilot channel pseudo-noise (PN) sequence on the forward link channel identified uniquely in the network by a pilot sequence offset and frequency assignment. It is possible to use the pilot channels of the active, candidate, neighboring and remaining sets, maintained in the target MS, for obtaining signal characteristic measurements (e.g., TOA and/or TDOA measurements) between the target MS 140 and the base stations in one or more of these sets.
- PN pilot channel pseudo-noise
- signal characteristic ranges or range differences related to the location of the ⁇ rget MS 140 can be calculated.
- TOA and/or TDOA ranges as exemplary, these ranges an then be input to either tk radius-radius multilateratio ⁇ or the time difference multilateration algorithms along with the known positions of the corresponding base stations 122 to thereby obtain one or more location estimates of the target MS 140. For example, if there are, four base stations 122 in the active set, the target MS 140 may cooperate with each of the base stations in this set to provide signal arrival time measurements.
- each of the resulting four sets of three of these base s ⁇ tions 122 may be used to provide an estimate of the target MS 140 as one skilled in the art will understand.
- location n be determined in either entity.
- TCSO FOMs may attempt to mitigate such ambiguity or inaccuracies by, e.g., identifying discrepancies (or consistencies) between arrival time measurements and other measurements (e.g., signal strength), these discrepancies (or consistencies) may be used to filter out at least those signal measurements and/or generated location estimates that appear less accurate.
- identifying and filtering may be performed by, for example, an expert system residing in the TCSO FOM.
- each of the target MS lo ⁇ tion estimates is used to generate a lo ⁇ tion hypothesis regardless of its apparent accuracy.
- these location hypotheses are input to an embodiment of the context adjuster 1326.
- each location hypothesis is adjusted according to past performance of its generating FOM 1224 in an area of the initial location estimate of the location hypothesis (the area, e.g., determined as a function of distance from this initial location estimate), this alternative embodiment adjusts each of the location hypotheses generated by a first order model according to a past performance of the model as applied to signal characteristic measurements from the same set of base stations 122 as were used in generating the location hypothesis.
- the retrieval retrieves the archived lo ⁇ tion estimates that are, in addition, derived from the signal characteristics measurement obtained from the same collection of base stations 122 as was used in generating the location hypothesis.
- the adjustment performed by this embodiment of the context adjuster 1326 adjusts according to the past performance of the distance model and the collection of base s ⁇ tions 122 used. Note in one embodiment, such adjustments can also be implemented using a precomputed vector lo ⁇ tion error gradient field.
- each of the location error vectors (as determined by past performance for the FOM) of the gradient field has its starting location ata lo ⁇ tion previously generated by the FOM, and to vector head at a corresponding verified location where the target MS 140 actually was.
- this embodiment determines or selects the location error vectors having starting locations within a small area (e.g., possibly of a predetermined size, but alternatively, dependent on the density of the lo ⁇ tion error vector starting locations nearby to the location hypothesis) of the location hypothesis. Additionally, the determination or selection may also be based upon a similarity of signal characteristics also obtained from the target MS 140 being lo ⁇ ted with signal characteristics corresponding to the starting locations of location error vectors of the gradient field. For example, such sign characteristics may be, e.g, time delay/signal strength multipath characteristics.
- Various mobile station location estimating models can be based on the angle of arrival (AOA) of wireless signals transmitted from a target MS 140 to the base station infrastructure as one skilled in the art will unders ⁇ nd.
- AOA angle of arrival
- Such AOA models typically require precise angular measurements of the wireless signals, and accordingly utilize specialized antennas at the base s ⁇ tions 122.
- the determined signal transmission angles are subject to multipath aberrations. Therefore, AOA is most effective when there is an unimpeded line-of-sight simultaneous transmission between the target MS 140 and at least two base stations 122.
- the Grubeck model includes a location estimator for determining more accurately the dis ⁇ nce between a wireless receiver at (RX), e.g., a CMRS fixed loration communication station (such as a BS 122) and a target MS 140, wherein wireless signals are repeatedly transmitted from the target MS 140 and may be subject to multipath.
- RX wireless receiver at
- An embodiment of the Grubeck model may be applied to TOA, TDOA, and/or AOA wireless measurements. For the TOA case, the following steps are performed:
- M is on the order of 50 to 100 (e.g., 70) wireless signal bursts, wherein each such burst contains a portion having an identical known contents of bits (denoted a training sequence).
- a different embodiment can use (e.g., 70) received bursts con ⁇ ining different (non-identical) information, but information still known to the RX.; (b) receiving the "M" signal samples s, along with multipath components and noise at, e.g., RX;
- each CPPi is determined by first determining, via a processor at the RX, a combined correlation response ("Channel Impulse Response” or CIRi) of a small number of the bursts (e.g., 5) by correlating each burst with its known contents. Accordingly; the squared absolute value of the CIRi is the "estimated channel power profile" or CPPi; (d) (randomly) selecting "N” (e.g., 10) out of the "M” received samples;
- CIRi Channel Impulse Response
- an embodiment of the Grubeck FOM may also be provides for TDOA and/or AOA wireless location techniques, wherein a similar incoherent integration may be performed. Note that a Grubeck FOM may be particularly useful for locating a target MS 140 in a GSM wireless network.
- a first order model 1224 is substantially disclosed in U.S. Patent 5,883,598 (denoted the '598 Patent herein) filed Dec.15, 1995 and issued Mar.16, 1999 having Parl, Bussgang, Weitzen and Zagami as inventors, this patent being fiilly incorporated herein by reference.
- the Parl FOM includes a system for receiving representative signals (denoted also "locating signal(s)") from the target MS 140 via, e.g., base s ⁇ tions 122 and subsequently combines information regarding the amplitude and phase of the MS transmitted signals received at the base s ⁇ tions to determine the position of the target MS 140.
- the Parl model uses input from a lo ⁇ ting signal having two or more single-frequency tones, as one skilled in the art will understand.
- the base s ⁇ tions 122 preferably includes at least two antennas spaced from each other by a dis ⁇ nce between a quarter wavelength and several wavelengths of the wireless locating signals received from the target MS 140.
- another antenna vertically above or below the two or more antennas also spaced by a dis ⁇ nce of between a quarter wavelength and several wavelengths can be used where elevation is also being estimated.
- the base s ⁇ tions 122 sample locating signals from the target MS 140.
- the locating signals include tones that can be at different frequencies.
- the tones can also be transmitted at different times, or, in an alternative embodiment, they can be transmitted simultaneously. Because, in one embodiment, only single-frequency tones are used as the lo ⁇ ting signal instead of modulated signals, substantial transmission circuitry may be eliminated.
- the Parl FOM extracts information from each representative signal received from a ⁇ rget MS 144, wherein at least some of the extracted information is related to the amplitude and phase of the received signal.
- the MS's lo ⁇ tion an be initially (roughly) determined by signal direction finding techniques. For example, an estimate of the phase difference between the signals at a pair of antennas at any BS 122 (having two such antennas) can lead to the determination of the angle from the base station to the target MS 140, and thus, the determination of the target MS direction.
- an enhanced lo ⁇ tion of the target MS 140 is computed directly from received target MS signal data using an ambiguity function A(x,y) described in the '598 Patent, wherein for each point at x,y, the ambiguity function A(x,y) depends upon the probability that the MS is located at the geolocation represented by (x,y).
- the Parl FOM combines angle of arrival related data and TDOA related data for ob ⁇ ining an optimized estimate of the target MS 140.
- independent AOA and TDOA MS lo ⁇ tions are not used in determining a resulting target MS location (e.g., without the need for projecting lines at angles of arrival or computing the intersection of hyperbolas defined by pairs of base s ⁇ tions).
- the Parl FOM estimates the ⁇ rget MS's location by minimizes a joint probability of location related errors.
- minimization may use the mean square error, and the location (x, y) atwhich minimization occurs is ⁇ ken as the estimate of the target MS 140.
- the ambiguity function A(x,y) defines the error involved in a position determination for each point in a geolocation (artesian coordinate system.
- the Parl model optimizes the ambiguity function to select a point x,y at which the associated error is minimized.
- the resulting lo ⁇ tion for (x, y) is ⁇ ke ⁇ as the estimate of the location of the ⁇ rget MS 140. Any of several different optimization procedures can be used to optimize the ambiguity function A(x,y).
- a fi ⁇ t rough estimate of the target MS's location may be ob ⁇ ined by direction finding (as discussed above). Hext, six points x,y may be selected that are in close proximity to the estimated point.
- the ambiguity function A(x,y) is solved for each of the x,y points to ob ⁇ in six values.
- the six computed values are then used to define a parabolic surface.
- the point x,y at which the maximum value of the parabolic surface occurs is then taken as the estimate of the ⁇ rget MS 140.
- optimization techniques may also be used. For example, a standard technique such as an iterative progression through trial and error to converge to the maximum can be used. Also, gradient search can be used to optimize the ambiguity function.
- the two-dimensional ambiguity function A(x,y) is extended to a three-dimensional function A(x,y,z).
- the ambiguity function may be optimized to select a point x,y,z as the best estimate of the ⁇ rget MS's location in three dimensions.
- any of several known optimization procedures such as iterative progression through trial and error, gradient search, etc, can be used to optimize the ambiguity function.
- ⁇ rget MS 140 location related information can be ob ⁇ ined from an MBS 148 and/or one or more LBSs 152.
- location related information an be supplied to any FOM 1224 that is able to accept such information as input.
- pattern recognition and adaptive FOMs may accept such information.
- Patent 6,031,490 (denoted the '490 Patent herein) filed Dec.23, 1997 and issued Feb.29, 2000 having Fo ⁇ sen, Berg and Ghisler as invento ⁇ , this patent being fiilly incorporated herein fiilly by reference.
- a TCSO FOM (denoted the FORSSEN FOM herein) using TDOA/AOA is disclosed in the '490 Patent.
- the FORSSEN FOM includes a location estimator for determining the Time Difference of Arrival (TDOA) of the position of a ⁇ rget MS 140, which is based on Time of Arrival (TOA) and/or AOA measurements.
- This FOM uses data received from "measuring devices" provided within a wireless telecommunications network.
- the measuring devices measure TOA on demand and (optionally) Direction of Arrival (DOA), on a digi ⁇ l uplink time slot or on digi ⁇ l information on an analog uplink traffic channel in one or more radio base s ⁇ tions.
- DOA Direction of Arrival
- the TOA and DOA information and the traffic channel number are reported to a Mobile Services Switching Center (MSC), which obtains the identity of the nrit MS 140 from the traffic channel number and sends the terminal identity and TOA and DOA measurement information to a Service Node (e.g., location center 142) of the network.
- the Service Node calculates the position of the ⁇ rget MS 140 using the TOA information (supplemented by the DOA information when available).
- the TLME model may utilize data from a second mobile radio terminal is colocated on a mobile platform (auto, emergency vehicle, etc.) with one of the radio base s ⁇ tions (e.g., MBS 148), which can be moved into relatively close proximity with tk target MS 140. Consequently, by moving one of the radio base stations (MBSs) close to the region of interest (near the ⁇ rget MS 140), the position determination accuracy is significantly improved.
- the '490 Patent also discloses techniques for rising the target MS's transmission power for thereby allowing wireless signals from the target MS to be better detected by dis ⁇ nt BSs 122.
- Radio coverage area of individual base s ⁇ tions 122 may be used to generate location estimates of the ⁇ rget MS 140.
- a first order model 1224 based on this notion may be less accurate than other techniques, if a reasonably accurate RF coverage area is known for each (or most) of the base s ⁇ tions 122, then such a FOM (denoted hereinafter as a "coverage area fi ⁇ t order model” or simply “coverage area model”) may be very reliable.
- loration coverage should be based on an MS's ability to adequately detect the pilot channel, as opposed to adequate signal quality for purposes of carrying user-accep ⁇ ble traffic in the voice channel.
- the "Location Coverage Area” will generally be a larger area than that of a typical "Voice (overage Area", although industry studies have found some occurrences of "no-coverage" areas within a larger covered area
- the approximate maximum RF coverage area for a given sector of (more generally angular range about) a base station 122 may be represented as a set of points representing a polygonal area (potentially with, e.g., holes therein to account for dead zones and/or notches). Note that if such polygonal RF coverage area representations can be reliably determined and maintained over time (for one or more BS signal power level settings), then such represen ⁇ tions an be used in providing a set theoretic or Venn diagram approach to estimating the lo ⁇ tion of a target MS 140. (overage area fi ⁇ t order models utilize such an approach.
- a coverage area model utilizes both the detection and non-detection of base s ⁇ tions 122 by the ⁇ rget MS 140 (conversely, of the MS by one or more base s ⁇ tions 122) to define an area where the target MS 140 may likely be.
- a relatively straightforward appli ⁇ tion of this technique is to:
- each inte ⁇ ection must include a predetermined number of the reliable RF coverage area represen ⁇ tions (e.g.,2or3) ;
- the new areas may be used to generate location hypotheses. Satellite Signal Triangulation First Order Models
- a target MS 140 e.g, GPS, GLONASS, LEOs, and MEOs.
- location estimates can be very accurate, and accordingly such accuracy would be reflected in the present invention by relatively high confidence values for the location hypotheses generated from such models in comparison to other FOMs.
- a first order model 1224 is disclosed in U.S. Patent 5,982,324 filed May 14, 1998 and issued Nov.9, 1999 having Waiters, Straw ⁇ ynski, and Steer as inventors, this patent being fiilly incorporated herein by reference.
- the WATTERS FOM includes a location estimator for determining the location of a ⁇ rget MS 140 using satellite signals to the ⁇ rget MS 140 as well as delay in wireless signals communicated between the ⁇ rget MS and base s ⁇ tions 122. For example, aspects of global positioning system (GPS) technology and cellular technology are combined in order to lo ⁇ te a ⁇ rget MS 140.
- GPS global positioning system
- the WATTERS FOM may be used to determine ⁇ rget MS location in a wireless network, wherein the network is utilized to collect differential GPS error correction da ⁇ , which is forwarded to the ⁇ rget MS 140 via the wireless network.
- the target MS 140 (which includes a receiver R for receiving non-terrestrial wireless signals from, e.g, GPS, or other satellites, or even airborne craft) receives this da ⁇ , along with GPS pseudoranges using its receiver R, and calculates its position using this information.
- a pseudosatellite signal broadcast from a BS 122 of the wireless network, is received by the target MS 140 and processed as a substitute for the missing satellite signal.
- the target MS's lo ⁇ tion is calculated using the wireless network infrastructure via TDOA/TOA with the BSs 122 of the network.
- the ⁇ rget MS is again calculated using wireless signals from the non-terrestrial wireless transmitters.
- the WATTERS FOM may use wireless signals already being transmitted from base s ⁇ tions 122 to the ⁇ rget MS 140 in wireless network to calculate a round trip time delay, from which a distance calculation between the base station and the target MS an be made.. This dis ⁇ nce calculation substitutes for a missing non-terrestrial transmission signal.
- LBS lo ⁇ tion base station
- AOM 1224 a database is accessed which con ⁇ ins electrical, radio propagation and coverage area characteristics of each of the location base s ⁇ tions in the radio coverage area.
- the LBS model is an active model, in that it can probe or excite one or more particular LBSs 152 in an area for which the ⁇ rget MS 140 to be located is suspected to be placed. Accordingly, the LBS model may receive as input a most likely ⁇ rget MS 140 location estimate previously output by the location engine 139 of the present invention, and use this location estimate to determine which (if any) LBSs 152 to activate and/or deactivate for enhancing a subsequent location estimate of the target MS.
- the feedback from the activated LBSs 152 may be provided to other FOMs 1224, as appropriate, as well as to the LBS model.
- it is an important aspett of the LBS model that when it receives such feedback, it may output lo ⁇ tion hypotheses having relatively small target MS 140 lo ⁇ tion area estimates about the active LBSs 152 and each such location hypothesis also has a high confidence value indicative of the target MS 140 positively being in the corresponding lo ⁇ tion area estimate (e.g, a confidence value of .9 to +1), or having a high confidence value indicative of the ⁇ rget MS 140 not being in the corresponding lo ⁇ tion area estimate (i.e., a confidence value of -0.9 to -l).
- these embodiments may have functionality similar to that of the coverage area first order model described above. Further note that for LBSs within a neighborhood of the ⁇ rget MS wherein there is a reasonable chance that with movement of the target MS may be detected by these LBSs, such LBSs may be requested to periodically activate. (Note, that it is not assumed that such LBSs have an on-line external power source; e.g., some may be solar powered).
- an LBS 152 includes sufficient electronics to carry voice communication with the target MS 140 and is the primary BS for the ⁇ rget MS (or alternatively, in the active or ⁇ ndidate set), then the LBS model will not deactivate this particular LBS during its procedure of activating and deactivating various LBSs 152.
- the stochastic fi ⁇ t order models may use statistical prediction techniques such as principle decomposition, partial least squares, partial least squares, or other regression techniques for predicting, for example, expected minimum and maximum distances of the target MS from one or more base s ⁇ tions 122, e.g, Bollenger Bands. Additionally, some embodiments may use Markov processes and Random Walks (predicted incremen ⁇ l MS movement) for determining an expected area within which the ⁇ rget MS 140 is likely to be. That is, such a process measures the incremental time differences of each pilot as the MS moves for predicting a size of a lo ⁇ tion area estimate using past MS estimates such as the verified location signatures in the lo ⁇ tion signature da ⁇ base 1320.
- FOMs 1224 using pattern recognition or associativity techniques there are many such techniques available. For example, there are statistically based systems such as "CART" (acronym for Classification and Regression Trees) by ANGOSS Software International Limited of Toronto, Canada that may be used for automatically for detecting or recognizing patterns in data thatwere not provided (and likely previously unknown). Accordingly, by imposing a relatively fine mesh or grid of cells of the radio coverage area, wherein each cell is entirely within a particular area type categorization, such as the transmission area types (discussed in the section, "Coverage Area: Area Types And Their Determination" above), the verified location signature clusters within the cells of each area type may be analyzed for signal characteristic patterns.
- area type categorization such as the transmission area types (discussed in the section, "Coverage Area: Area Types And Their Determination” above)
- Such a characteristic pattern can be used to identify one or more of the cells in which a ⁇ rget MS is likely to be located. That is, one or more location hypotheses may be generated having ⁇ rget MS 140 lo ⁇ tion estimates that cover an area having the identified cells wherein the target MS 140 is likely to be located.
- Such statistically based pattern recognition systems as "CART" include software code generators for generating expert system software embodiments for recognizing the patterns detected within a training set (e.g., the verified location signature clusters).
- a related statistical pattern recognition FOM 1224 is also disclosed in U.S. Patent 6,026304, filed Jan.8, 1997 and issued Feb.15, 2000, having Hilsenrath and Wax as inventors, this patent (denoted the Hilsenrath patent herein) being incorporated herein fully by reference.
- An embodiment of a FOM 1224 based on the disclosure of the Hilsenrath patent is referred to herein as the Hilsenrath FOM.
- the Hilsenrath FOM includes a wireless location estimator that locates a ⁇ rget MS 140 using measurements of multipath signals in order to accurately determine the location of the ⁇ rget MS 140.
- the Hilsenrath FOM uses wireless measurements of both a direct signal transmission path and multipath transmission signals from the MS 140 to a base station 122 receiver.
- the wireless signals from the ⁇ rget MS 140 arrive at and are detected by an antenna array of the receiver at the BS 122, wherein the antenna array includes a plurality of antennas.
- a signal signature (e.g., an embodiment of a location signature herein) for this FOM may be derived from any combination of amplitude, phase, delay, direction, and polarization information of the wireless signals transmitted from the ⁇ rget MS 140 to the base station 122 receiver.
- the Hilsenrath FOM 1224 determines a signal signature from a signal subspace of a covariance matrix.
- the eigenvalues of R whose magnitudes exceed a predetermined threshold determine a set of dominant eigenvecton.
- the signal subspace is the space spanned by these dominant eigenvectors.
- the signal signature is compared to a database of calibrated signal signatures and corresponding locations (e.g., an embodiment of the location signature da ⁇ base 1320), wherein the signal signatures in the da ⁇ base include representations of the signal subspaces (such as the dominant eigenvectors ofthecovariance matrices. Accordingly, a location whose ⁇ librated signature best matches the signal signature of the ⁇ rget MS 140 is selected as the most likely location of the ⁇ rget MS 140.
- the da ⁇ base of calibrated signal signatures and corresponding verified lo ⁇ tions is generated by a calibration procedure in which a calibrating MS 140 transmits location da ⁇ derived from a co-located GPS receiver to the base s ⁇ tions 122.
- the location has associated therewith: the (GPS or verified) location information and the corresponding signal signature of the calibrating MS 140.
- the location of a target MS 140 in the service area may be determined as follows. Signals originating from the ⁇ rget MS 140 at an unknown location are received at a base station 122. A signal processor, e.g, at the base station 122, then determines the signal signature as described above. The signal signature is then compared with the calibrated signal signatures stored in the above described embodiment of the loration signature da ⁇ base 1320 during the calibration procedure. Using a measure of difference between subspaces (e.g, an angle between subspaces), a set of likely lo ⁇ tions is selected from this location signature da ⁇ base embodiment. These selected likely locations are those locations whose associated ⁇ librated signal signatures differ by less than a minimum threshold value from the ⁇ rget MS 140 signal signature.
- a measure of difference between subspaces e.g, an angle between subspaces
- the difference measure is further used to provide a corresponding measure of the probability that each of the selected likely locations is the actual target MS lo ⁇ tion. Moreover, for one or more of the selected likely location, the corresponding measure may be output as the confidence value for a corresponding location hypothesis output by a Hilsenrath FOM 1224.
- an embodiment of the present invention using such a Hilsenrath FOM 1224 performs the following steps (a) - (d):
- step of comparing comprises substep of calculating differences between: (i) the measured subspace, and (ii) a similarly determined subspace for each of a plurality of the previously ob ⁇ ined signal signatures;
- FOMs may not be exceedingly accurate, but may be very reliable.
- an aspect of at least some embodiments of the present invention is to use a plurality of MS location techniques (FOMs) for generating location estimates and to analyze the generated estimates (likely after being adjusted) to detect patterns of convergence or clustering among the estimates, even large MS location area estimates may be useful.
- FOMs MS location techniques
- another statistically based FOM 1224 may be provided wherein the radio coverage area is decomposed substantially as above, but in addition to using the signal characteristics for detecting useful signal patterns, the specific identifications of the base station 122 providing the signal characteristics may also be used.
- an expert system may be generated that outputs a target MS 140 location estimate that may provide both a reliable and accurate lo ⁇ tion estimate of a ⁇ rget MS 140.
- a da ⁇ processing component that can modify in da ⁇ processing behavior in response to certain inputs that are used to change how subsequent inputs are processed by the component.
- a da ⁇ processing component may be "explicitly adaptive” by modifying to behavior according to the input of explicit instructions or control da ⁇ that is input for changing the component's subsequent behavior in ways that are predic ⁇ ble and expected. That is, the input encodes explicit instructions that are known by a user of the component.
- a da ⁇ processing component may be "implicitly adaptive" in that its behavior is modified by other than instructions or control data whose meaning is known ⁇ a user of the component.
- such implicitly adaptive da ⁇ processo ⁇ may learn by training on examples, by substantially unguided exploration of a solution space, or other da ⁇ driven adaptive strategies such as statistically generated decision trees. Accordingly, it is an aspect of the present invention to utilize not only explicitly adaptive MS location estimators within FOMs 1224, but also implicitiy adaptive MS location estimators.
- artificial neural networks also denoted neural nets and ANNs herein
- implicitly adaptive MS lo ⁇ tion estimators within FOMs are used in some embodiments as implicitly adaptive MS lo ⁇ tion estimators within FOMs.
- Artificial neural networks may be particularly useful in developing one or more first order models 1224 for locating an MS 140, since, for example, ANNs can be trained for classifying and/or associatively pattern matching of various RF signal measurements such as the location signatures. That is, by training one or more artificial neural nett using RF signal measurements from verified locations so that RF signal transmissions characteristics indi ⁇ tive of particular locations are associated with their corresponding lo ⁇ tions, such trained artificial neural nets can be used to provide additional ⁇ rget MS 140 location hypotheses. Moreover, it is an aspect of the present invention that the training of such artificial neural net based FOMs (ANN FOMs) is provided without manual intervention as will be discussed hereinbelow.
- ANN FOMs artificial neural net based FOMs
- U.S. patent 5390339 filed Oct.23, 1991 having an issue date of Feb.14, 1995 with inventor being Bruckert et. al. provides number of embodiments of wireless location estimators for estimating the location of a "remote unit.”
- various lo ⁇ tion estimator embodiments are described in relation to Figs. iB and 2B therein.
- the location estimators in the '339 patent are, in general, directed to determining weighted or adjusted dis ⁇ ces of the "remote unit” (e.g, MS 140) from one or more "transceivers” (e.g, base s ⁇ tions 122).
- the dis ⁇ nces are determined using signal strength measurements of wireless signals transmitted between the "remote unit” and the “transceivers.” However, adjustments are in the signal strengths according to various signal transmission anomalies (e.g, co-channel interference), impairments and/or errors. Additionally, a signal RF propagation model may be utilized, and a likelihood of the "remote unit” being in the designated coverage areas (cells) of particular transceivers (e.g., base s ⁇ tions 122) is determined using probabilistic techniques such as posteriori probabilities. Accordingly, the Bruckert '339 patent is fully incorporated by reference herein and may con ⁇ in essential material for the present
- the location processing of the present invention focuses on the ability to predict and model RF contours using actual RF measurements, then performing da ⁇ reduction techniques such as curve fitting technique, Bollinger Bands, and Genetic Algorithms, in order to locate a mobile unit and disseminate to location.
- da ⁇ reduction techniques such as curve fitting technique, Bollinger Bands, and Genetic Algorithms
- the LeBlanc '412 patent is fiilly incorporated by reference herein and may con ⁇ in essential material for the present invention.
- U.S. patent 5,293,645 ('645 patent) filed Oct.4, 1991 having an issue date of March 8, 1994 with inventor Sood. provide further embodiments of wireless location estimators that may be used as First Order Models 1224.
- the '645 patent describes wireless location estimating techniques using trianplations or other geographical inte ⁇ ection techniques.
- a first order model 1224 denoted the ⁇ ost model herein.
- the Yost model includes a location estimator that uses a combination of
- Time Difference of Arrival (TDOA) and Timing Advance (TA) location determining techniques for determining the location of a ⁇ rget MS 140, wherein there are minor modifications to a telecommunication network such as a CMRS.
- the hybrid wireless location technique utilized by this location estimator uses TDOA measurements and TA measurements to obtain substantially independent location estimates of the ⁇ rget MS 140, wherein the TDOA measurements determine hyperbolae MS loci, about base stations 122 communicating (uni or bi-directionally) with the target MS, and the TA measuremenn determine circles about the base s ⁇ tions 122.
- an enhanced location estimate of the MS 140 can be ob ⁇ ined by using a least squares (or other statistical technique), wherein the least-squares technique determines a lo ⁇ tion for the MS between the various curves (hyperbolae and circles) that best approximates a point of intersection.
- TA is used in all Time Division Multiple Access (TDMA) systems as one skilled in the art will understand, and measuremenn of TA can provide a measurement of the dis ⁇ nce of the MS from a TDMA communication station in communication with the ⁇ rget MS 140.
- TDMA Time Division Multiple Access
- measuremenn of TA can provide a measurement of the dis ⁇ nce of the MS from a TDMA communication station in communication with the ⁇ rget MS 140.
- the Yost model is disclosed in ⁇ .S.
- Patent 5,987329 filed July 30, 1997 and issued Nov.16, 1999 having Yost and Panchapakesan as inventors, this patent being fiilly incorporated herein fiilly by reference to thereby further describe the Yost model.
- the following quote from the '329 Patent describes an important aspect of the Yost model: "Furthermore, the combination of TA and TDOA allows resolution of common ambiguities suffered by either technique separately. For example, in FIG.5 a situation involving three base s ⁇ tions 24 (A, B and C as described, the latter being visible in the figure) is represented along with the resul ⁇ nt two hyperbolas AB and AC (and redundant hyperbola BC) for a TDOA position determination of the mobile M.
- FIG.5 is a magnified view of the mobile terminal M lo ⁇ tion showing the nearby base s ⁇ tions and the nearby portions at the curves.
- TDOA timing advance
- the multiple location estimator architecture of the present invention may substantially include the Yost model whenever both the TA FOM and TDOA FOM are both activated for a same location instance of a target MS 140.
- a first order model 1224 denoted the Sheynblat model (FOM) herein, is disclosed in U.S. Patent 5,999,124 (denoted the "124 Patent herein) filed April 22, 1998 and issued Dec.7, 1999 having Sheynblat as the inventor, this patent being fiilly incorporated herein by reference
- the Sheynblat FOM provides a location estimator for processing target MS 140 location related information ob ⁇ ined from: (a) satellite signals of a satellite positioning system (denoted SPS in the '124 Patent) (e.g., GPS or GLONASS, LEO positioning satellites, and/or MEO positioning satellites), and (b) communication signals transmitted in the terrestrial wireless cellular network of BSs 122 for a radio coverage area, e.g., coverage area 120 (Fig.4), wherein there is two-way wireless communication between the ⁇ rget MS 140 and the BSs.
- a satellite positioning system denoted SPS in the '124 Patent
- GPS or GLONASS L
- the lo ⁇ tion related information ob ⁇ ined from the satellite signals includes a representation of a time of travel of SPS satellite signals from a SPS satellite to a corresponding SPS receiver operatively coupled to (and co-lo ⁇ ted with) the target MS 140 (such "time of travel” is referred to as a pseudorange to the SPS satellite),
- the location related information ob ⁇ ined from the communication signals in the wireless cellular network includes time of travel related information for a message in the communication signals between a BS 122 transceiver and the target MS 140 (this second "time of travel" related information is referred to as a cellular pseudorange).
- various combinations of pseudoranges to SPS satellites, and cellular pseudoranges can be used to determine a likely location of the target MS 140.
- the target MS 140 enhanced with a SPS receiver
- the ⁇ rget MS is also in wireless communication (or can be in wireless communi ⁇ tion) with two BSs 122
- three pseudoranges may be ob ⁇ ined and used to determine the position of the ⁇ rget MS by, e.g., trianguiation.
- other combinations are possible for determining a location of the target MS 140, e.g., pseudoranges to two SPS satellites and one cellular pseudorange.
- ⁇ rget MS 140 may detect (or be detected by) a plurality of BSs 122, a corresponding plurality of cellular pseudoranges may be ob ⁇ ined, wherein such cellular psuedoranges may be used in a cluster analysis technique to disambiguate MS locations identified by the satellite pseudoranges.
- the determination of a location hypothesis is performed, in at least one embodiment, at a site remote from the target MS 140, such as the lo ⁇ tion center/gateway 142, or another site that co muni ⁇ tes with the lo ⁇ tion center/gateway for supplying a resulting MS location to the gateway.
- the ⁇ rget MS 140 may perform the calculations to determine its own location. Note that this alternative technique may be particularly useful when the target MS 140 is a mobile base station 148.
- the MS status repository 1338 is a run-time storage manager for storing location hypotheses from previous activations of the location engine 139 (as well as the output target MS location estimate ⁇ )) so that a target MS may be tracked using ⁇ rget MS location hypotheses from previous location engine 139 activations to determine, for example, a movement of the ⁇ rget MS between evaluations of the ⁇ rget MS location.
- ⁇ rget MS location hypotheses from previous location engine 139 activations to determine, for example, a movement of the ⁇ rget MS between evaluations of the ⁇ rget MS location.
- these hypotheses may be used to resolve conflicts between hypotheses in a current attivation for locating the ⁇ rget MS; e.g, MS paths may be stored here for use in extrapolating a new location
- Any collection of mobile electronics (denoted mobile location unit) that is able to both estimate a location of a target MS 140 and communicate with the base s ⁇ tion network may be utilized by the present invention to more accurately locate the target MS.
- Such mobile location unto may provide greater ⁇ rget MS location accuracy by, for example, homing in on the target MS and by transmitting additional MS location information to the location center 142.
- the electronics of the mobile location unit may be little more than an onboard MS 140, a settored/direttional antenna and a controller for communicating between them.
- the onboard MS is used to communicate with the lo ⁇ tion center 142 and possibly the ⁇ rget MS 140, while the antenna monitors signals for homing in on the ⁇ rget MS 140.
- a GPS receiver may also be incorporated so that the lo ⁇ tion of the mobile location unit may be determined and consequently an estimate of the location of the target MS may also be determined.
- such a mobile location unit is unlikely to be able to determine substantially more than a direction of the target MS 140 via the sectored/directional antenna without further base s ⁇ tion infrastructure cooperation in, for example, determining the transmission power level of the ⁇ rget MS or varying this power level.
- the present invention includes a mobile location unitthat is also a scaled down version of a base s ⁇ tion 122.
- an enhanced autonomous MS mobile location system can be provided that can be effectively used in, for example, emergency vehicles, air planes and boats. Accordingly, the description that follows below describes an embodiment of an MBS 148 having the above mentioned componenn and capabilities for use in a vehicle. As a consequence of the MBS 148 being mobile, there are fundamental differences in the operation of an MBS in comparison to other types of BS's 122 (152).
- MBSs may be used in areas (such as wilderness areas) where there may be no other means for reliably and cost effettively locating a target MS 140 (i.e., there may be insufficient fixed location BS's coverage in an area).
- Fig.11 provides a high level block diagram architecture of one embodiment of the MBS location subsystem 1508.
- an MBS may include componenn for communicating with the fixed location BS network infrastructure and the location center 142 via an on-board transceiver 1512 that is effettively an MS 140 integrated into the location subsystem 1508.
- the MBS 148 may not be able to communicate reliably with the location center ⁇ (e.g., in rural or oun ⁇ inous areas having reduced wireless telephony coverage). So it is desirable that the MBS 148 must be capable of functioning substantially autonomously from the location center.
- each MBS 148 must be ⁇ pable of estimating both in own location as well as the location of a ⁇ rget MS 140.
- many commercial wireless telephony technologies require all BS's in a network to be very accurately time synchronized both for transmitting MS voice communi ⁇ tion as well as for other services such as MS lo ⁇ tion. Accordingly, the MBS 148 will also require such time synchronization.
- an MBS 148 may not be in cons ⁇ nt communication with the fixed location BS network (and indeed may be off-line for substantial periods of time), on-board highly accurate timing device may be necessary.
- such a device may be a commercially available ribidium oscillator 1520 as shown in Fig.11.
- the MBS 148 includes a scaled down version of a BS 122 (denoted 1522 in Fig.11), it is ⁇ pable of performing most typical BS 122 asks, albeit on a reduced scale.
- the base station portion of the MBS 148 can:
- (c) be the primary BS 122 for an MS 140, and consequently be in voice communication with the target MS (via the MBS operator telephony interface 1524) if the MS supports voice communication.
- the MBS 148 can, if it becomes the primary base s ⁇ tion communicating with the MS 140, request the MS to raise/lower to power or, more generally, control the communication with the MS (via the base s ⁇ tion componenn 1522).
- the pilot channel for the MBS is preferably a nonstandard pilot channel in that itshould not be identified as a conventional telephony traffic bearing BS 122 by MS's seeking normal telephony communication.
- a target MS 140 requesting to be lo ⁇ ted may, depending on in capabilities, either automati ⁇ lly configure itself to scan for certain predetermined MBS pilot channels, or be instructed via the fixed location base s ⁇ tion network (equivalently BS infrastructure) to scan for a certain predetermined MBS pilot channel.
- the MBS 148 has an additional advantage in that it can substantially increase the reliability of communication with a target MS 140 in comparison to the base s ⁇ tion infrastructure by being able to move toward or track the target MS 140 even if this MS is in (or moves into) a reduced infrastructure base s ⁇ tion network coverage area.
- an MBS 148 may preferably use a directional or smart antenna 1526 to more accurately locate a direction of signals from a ⁇ rget MS 140.
- the sweeping of such a smart antenna 1526 (physically or electronically) provides directional information regarding signals received from the ⁇ rget MS 140. That is, such directional information is determined by the signal propagation delay of signals from the ⁇ rget MS 140 to the angular sectors of one of more directional antennas 1526 on-
- this example describes the high level computational sates through which the MBS 148 transitions, these sates also being illustrated in the sate transition diagram of Fig.12. Note that this figure illustrates the primary s te transitions between these MBS 148 sates, wherein the solid sate transitions are indicative of a typical "ideal" progression when locating or tracking a ⁇ rget MS 140, and the dashed state transitions are the primary sate reve ⁇ ions due, for example, to difficulties in locating the target MS 140.
- the MBS 148 may be in an inactive sate 1700, wherein the MBS loation subsystem 1508 is effectively available for voice or da ⁇ communi ⁇ tion with the fixed location base station network, but the MS 140 lorating ⁇ pabilities of the MBS are not active.
- the MBS e.g., a police or rescue vehicle
- the MBS may enter an active sate 1704 once an MBS operator has logged onto the MBS loration subsystem of the MBS, such logging being for authentication, verification and journaling of MBS 148 evenn.
- the MBS may be listed by a 911 emergency center and/or the lo ⁇ tion center 142 as eligible for service in responding to a 911 request.
- the MBS 148 may transition to a ready sate 1708 signifying that the MBS is ready for use in locating and/or intercepting a ⁇ rget MS 140. That is, the MBS 148 may transition to the ready state 1708 by performing the following steps:
- (la) Synchronizing the timing of the lo ⁇ tion subsystem 1508 with that of the base s ⁇ tion network infrastructure.
- the MBS 148 when requesting such time synchronization from the base station infrastructure, the MBS 148 will be at a predetermined or well known location so thatthe MBS time synchronization may adjust for a known amount of signal propagation delay in the synchronization signal.
- (lb) Establishing the location of the MBS 148. In one embodiment, this may be accomplished by, for example, an MBS operator identifying the predetermined or well known lo ⁇ tion at which the MBS 148 is located, (ic) Communicating with, for example, the 911 emergency center via the fixed location base station infrastructure to identify the MBS 148 as in the ready state.
- the MBS 148 While in the ready state 1708, as the MBS 148 moves, it has its location repeatedly (re)- ⁇ stimated via, for example, GPS signals, location center 142s location estimates from the base s ⁇ tions 122 (and 152), and an on-board deadreckoning subsystem 1527 having an MBS location estimator according to the programs described hereinbelow.
- the accuracy of the base station time synchronization (via the ribidiu oscillator 1520) and the accuracy of the MBS 148 lo ⁇ tion may need to both be periodically recalibrated according to (1a) and (lb) above.
- a 911 signal is transmitted by a ⁇ rget MS 140
- this signal is transmitted, via the fixed location base station infrastructure, to the 911 emergency center and the location center ⁇
- the MBS 148 is in the ready sate 1708
- the MBS may transition to a seek s te 1712 by performing the following steps: (2a) Communicating with, for example, the 911 emergency response center via the fixed location base s ⁇ tion network to receive the PN code for the ⁇ rget MS to be located (wherein this communication is performed using the MS-like transceiver 1512 and/or the MBS operator telephony interface 1524).
- the MBS 148 may commence toward the ⁇ rget MS location estimate provided. Note that it is likely that the MBS is not initially in direct signal contact with the ⁇ rget MS. Accordingly, in the seek state 1712 the following steps may be, for example, performed: (3a) The lo ⁇ tion center ⁇ or the 911 emergency response center may inform the target MS, via the fixed lo ⁇ tion base station network, to lower in threshold for soft hand-off and at least periodically boost to loration signal strength. Additionally, the ⁇ rget MS may be informed to scan for the pilot channel of the MBS 148.
- the MBS repeatedly provides the MBS operator with new ⁇ rget MS location estimates provided substantially by the lo ⁇ tion center via the fixed location base station network.
- the MBS 148 repeatedly attempts to detect a signal from the ⁇ rget MS using the PN code for the target MS.
- the MBS 148 repeatedly estimates in own location (as in other states as well), and receives MBS location estimates from the location center.
- the MBS 148 and ⁇ rget MS 140 detect one another (which typically occurs when the two unto are within .25 to 3 miles of one another), the MBS enters a contact sate 1716 when the target MS 140 enters a soft hand-off sate with the MBS. Accordingly, in the conact state 1716, the following steps are, for example, performed: (4a) The MBS 148 repeatedly estimates in own lo ⁇ tion. (4b) Repeatedly, the location center ⁇ provides new ⁇ rget MS 140 and MBS location estimates to the MBS 148 via the fixed location base infrastructure network.
- the MBS 148 Since the MBS 148 is at least in soft hand-off with the ⁇ rget MS 140, the MBS can estimate the direction and dis ⁇ nce of the target MS itself using, for example, detetted ⁇ rget MS signal strength and TOA as well as using any recent lo ⁇ tion center ⁇ rget MS location estimates. (4d) The MBS 148 repeatedly provides the MBS operator with new ⁇ rget MS location estimates provided using MS location estimates provided by the MBS itself and by the location center via the fixed lo ⁇ tion base station network. When the ⁇ rget MS 140 detecn that the MBS pilot channel is sufficiently strong, the target MS may switch to using the MBS 148 as in primary base s ⁇ tion. When this occu ⁇ , the MBS enters a control sate 1720, wherein the following steps are, for example, performed: (5a) The MBS 148 repeatedly estimates in own location.
- the location center 142 provides new ⁇ rget MS and MBS location estimates to the MBS 148 via the network of base stations 122 (152).
- the MBS 148 estimates the direction and dis ⁇ nce of the ⁇ rget MS 140 itself using, for example, detected ⁇ rget MS signal strength and
- the MBS 148 repeatedly provides the MBS operator with new target MS location estimates provided using MS location estimates provided by the MBS itself and by the location center 142 via the fixed lo ⁇ tion base s ⁇ tion network.
- the MBS 148 becomes the primary base s ⁇ tion for the ⁇ rget MS 140 and therefore controls at least the signal strength output by the target MS. Note, there an be more than one MBS 148 tracking or lo ⁇ ting an MS 140. There can also be more than one ⁇ rget MS 140 to be tracked concurrently and each target MS being tracked may be stationary or moving.
- An MBS 148 uses MS signal charatteristic data for locating the MS 140.
- the MBS 148 may use such signal characteristic da ⁇ to facilitate determining whether a given signal from the MS is a "direct shot" or an multipath signal. That is, in one embodiment, the MBS 148 attempts to determine or detect whether an MS signal transmission is received directly, or whether the transmission has been reflected or deflected. For example, the MBS may determine whether the expected signal strength, and TOA agree in distance estimates for the MS signal transmissions. Note, other signal characteristics may also be used, if there are sufficient electronics and processing available to the MBS 148; i.e, determining signal phase and/or polarity as other indi ⁇ tions of receiving a "direct shot" from an MS 140.
- the MBS 148 (Fig.11) includes an MBS controller 1533 for controlling the location capabilities of the MBS 148.
- the MBS controller 1533 initiates and controls the MBS state changes as described in Fig.12.
- the MBS controller 1533 also communicates with the location controller 1535, wherein this latter controller controls MBS activities related to MBS location and ⁇ rget MS location.
- the io ⁇ tion controller 1535 receives da ⁇ inputfrom an event generator 1537 for generating event records to be provided to the location controller 1535.
- records may be generated from data input received from: (a) the vehicle movement detector 1539 indicating that the MBS 148 has moved at least a predetermined amount and/or has changed direction by at least a predetermined angle, or (b) the MBS signal processing subsystem 1541 indicating thatthe additional signal measurement da ⁇ has been received from either the location center 142 or the ⁇ rget MS 140.
- the MBS signal processing subsystem 1541 in one embodiment, is similar to the signal processing subsystem 1220 of the loration center 142. may have multiple command schedule ⁇ .
- a scheduler 1528 for commands related to communi ⁇ ting with the location center 142 a scheduler 1530 for commands related to GPS communi ⁇ tion (via GPS receiver 1531), a scheduler 1529 for commands related to the frequency and granularity of the reporting of MBS changes in direction and/or position via the MBS dead reckoning subsystem 1527 (note that this scheduler is potentially optional and that such commands may be provided directly to the deadreckoning estimator 1544), and a scheduler 1532 for communicating with the target MS(s) 140 being located.
- each MBS 148 has a plurality of MBS location estimators (or hereinafter also simply referred to as location estimators) for determining the location of the MBS.
- Each such location estimator computes MBS location information such as MBS location estimates, changes to MBS location estimates, or, an MBS location estimator may be an interface for buffering and/or translating a previously computed MBS location estimate into an appropriate format.
- the MBS lo ⁇ tion module 1536 which determines the lo ⁇ tion of the MBS, may include the following MBS lo ⁇ tion estimators 1540 (also denoted baseline location estimators): (a) a GPS location estimator 1540a (not individually shown) for computing an MBS location estimate using GPS signals,
- an MBS operator lo ⁇ tion estimator 1540c (not individually shown) for buffering and/or translating manual MBS lo ⁇ tion entries received from an MBS location operator, and (d) in some MBS embodiments, an LBS lo ⁇ tion estimator i54 ⁇ d (not individually shown) for the activating and deactivating of LBS's 152.
- LBS low cost loration base stations 152
- the MBS 148 may be able to quickly use the loration information relating to the lo ⁇ tion base s ⁇ tions for determining in location by using signal characteristics ob ⁇ ined from the LBSs 152.
- each of the MBS baseline location estimators 1540 provide an actual MBS location rather than, for example, a change in an MBS location.
- additional MBS baseline loration estimators 1540 may be easily integrated into the MBS location subsystem 1508 as such baseline location estimators become available.
- a baseline lo ⁇ tion estimator that receives MBS location estimates from reflective codes provided, for example, on streets or street signs can be straightforwardly incorporated into the MBS location subsystem 1508.
- MBS lo ⁇ tion technologies and their corresponding MBS location estimators are utilized due to the fact that there is currently no single loration technology available that is both sufficiently fast, accurate and accessible in subs ⁇ ntiaiiy all terrains to meet the location needs of an MBS 148.
- GPS technologies may be sufficiently accurate; however, GPS technologies: (a) may require a relatively long time to provide an initial location estimate (e.g, greater than 2 minutes); (b) when GPS communication is disturbed, it may require an equally long time to provide a new location estimate; (c) clouds, buildings and/or moun ⁇ ins can prevent location estimates from being ob ⁇ ined; (d) in some cases signal reflections can subs ⁇ ntiaiiy skew a location estimate.
- an MBS 148 may be able to use triangulation or rrilateralization technologies to ob ⁇ in a lo ⁇ tion estimate; however, this assumes that there is sufficient (fixed location) infrastructure BS coverage in the area the MBS is located.
- an MBS 148 is provided with a plurality of location technologies, each supplying an MBS location estimate.
- the following FOMs 1224 may have similar location models incorporated into the MBS:
- a variation of the artificial neural net based FOMs 1224 may be used to provide MBS lo ⁇ tion estimates via, for example, learned associations between fixed location BS signal characteristics and geographic locations;
- an LBS location FOM 1224 for providing an MBS with the ability to activate and deactivate LBS's to provide (positive) MBS location estimates as well as negative MBS location regions (i.e, regions where the MBS is unlikely to be since one or more LBS's are not detected by the MBS transceiver);
- MBS location reasoning agenn and/or a location estimate heuristic agents for resolving MBS lo ⁇ tion estimate conflicts and providing greater MBS location estimate accuracy.
- modules similar to the analytical reasoner module 1416 and the historical lo ⁇ tion reasoner module 1424 are similar to those MBS loration models requiring communi ⁇ tion with the base s ⁇ tion infrastructure.
- an alternative embodiment is to rely on the location center 142 to perform the compu ⁇ tions for at least some of these MBS FOM models.
- each of the MBS location models mentioned immediately above require communication with the network of fixed location BS's 122 (152), it may be advantageous to transmit MBS location estimating data to the location center 142 as if the MBS were another MS 140 for the location center to locate, and thereby rely on the location estimation capabilities at the location center rather than duplicate such models in the MBS 148.
- the advantages of this approach are that:
- an MBS is likely to require subs ⁇ ntiaiiy less memory, particularly for da ⁇ bases, than that of the lo ⁇ tion center.
- the confidence for a manual entry of location da ⁇ by an MBS operator may be rated the highest and followed by the confidence for (any) GPS location da ⁇ , followed by the confidence for (any) lo ⁇ tion center lo ⁇ tion 142 estimates, followed by the confidence for (any) lo ⁇ tion estimates using signal charatteristic data from LBSs.
- prioritization may vary depending on, for ins ⁇ nce, the radio coverage area 120.
- MBS location data received from the GPS and location center may vary according to the area in which the MBS 148 resides. That is, if it is known that for a given area, there is a reasonable probability that a GPS signal may suffer multipath distortions and thatthe location center has in the past provided reliable location estimates, then the confidences for these two location sources may be reversed.
- MBS operators may be requested to occasionally manually enter the location of the MBS 148 when the MBS is stationary for determining and/or calibrating the accuracy of various MBS loration estimators.
- the MBS 148 may use deadreckoning information provided by a deadreckoning MBS lo ⁇ tion estimator 1544 whereby the MBS may obtain MBS deadreckoning location change estimates.
- the deadreckoning MBS location estimator 1544 may use, for example, an on-board gyroscope 1550, a wheel rotation measurement device (e.g, odometer) 1554, and optionally an accelerometer (not shown).
- each deadreckoning MBS lo ⁇ tion estimator 1544 periodically provides at least MBS dis ⁇ nce and directional da ⁇ related to MBS movemenn from a most recent MBS location estimate. More precisely, in the absence of any other new MBS location information, the deadreckoning MBS location estimator 1544 outputs a series of . measuremenn, wherein each such measurement is an estimated change (or del ⁇ ) in the position of the MBS 148 between a request input timestamp and a closest time prior to the times ⁇ mp, wherein a previous deadreckoning terminated.
- each deadreckoning location change estimate includes the following fields:
- the "latest times ⁇ mp” is the times ⁇ mp input with a request for deadreckoning location da ⁇
- the "earliest times ⁇ mp” is the timestamp of the closest time, T, prior to the latesttimes ⁇ mp, wherein a previous deadreckoning output has in a times ⁇ mp at a time equal to T.
- the frequency of such measuremenn provided by the deadreckoning subsystem 1527 may be adaptively provided depending on the velocity of the MBS 148 and/or the elapsed time since the most recent MBS lo ⁇ tion update. Accordingly, the architecture of at least some embodimenn of the MBS lo ⁇ tion subsystem 1508 must be such that it an utilize such deadreckoning information for estimating the location of the MBS 148. In one embodiment of the MBS lo ⁇ tion subsystem 1508 described in further detail hereinbelow, the outputs from the deadreckoning MBS location estimator 1544 are used to synchronize MBS location estimates from different MBS baseline location estimators.
- such a deadreckoning output may be requested for substantially any time from the deadreckoning MBS location estimator, such an output an be requested for substantially the same point in time as the occurrence of the signals from which a new MBS baseline lo ⁇ tion estimate is derived. Accordingly, such a deadreckoning output an be used to update other MBS location estimates not using the new MBS baseline lo ⁇ tion estimate. It is assumed that the error with dead reckoning increases with deadreckoning dis ⁇ nce. Accordingly, it is an aspect of the embodiment of
- the deadreckoning MBS location estimator is periodically reset so that the error accumulation in to outpun can be decreased. In particular, such resetting occurs when there is a high probability that the location of the MBS is known.
- the deadreckoning MBS loration estimator may be reset when an MBS operator manually ente ⁇ an MBS location or verifies an MBS location, or a computed MBS location has sufficientiy high confidence.
- a first embodiment of the MBS loration subsystem architecture is somewhat different from the location engine 139 architecture. That is, the architecture of this first embodiment is simpler than that of the architecture of the location engine 139.
- the architecture of the location engine 139 may also be applied for providing a second embodiment of the MBS location subsystem 1508, as one skilled in the art will appreciate after reflecting on the architectures and processing provided at an MBS 148.
- an MBS loration subsystem 1508 architecture may be provided that has one or more first order models 1224 whose output is supplied to, for example, a blackboard or expert system for resolving MBS lo ⁇ tion estimate conflicts, such an architecture being analogous to one embodiment of the location engine 139 architecture.
- the MBS location subsystem architecture may also be applied as an alternative architecture for the lo ⁇ tion engine 139.
- each of the first order models 1224 may provide in MS location hypothesis outpun to a corresponding "location track," analogous to the MBS lo ⁇ tion tracks described hereinbelow, and subsequently, a most likely MS current location estimate may be developed in a "current lo ⁇ tion track" (also described hereinbelow) using the most recent lo ⁇ tion estimates in other loration tracks.
- the location estimating models of the location center 139 and those of the MBS 148 are may be interchanged depending on the where it is deemed most appropriate for such each such model to reside.
- various combinations of the location center location architecture and the mobile s ⁇ tion architecture may be utilized at either the location center or the MBS 148.
- the models described here for locating the MBS 148 can be used for locating other MSs 140 that are be capable of supporting transmission of wireless signal measuremenn that relate to models requiring the additional electronics available at the MBS 140 (e.g, GPS or other satellite signals used for location).
- the ideas and methods discussed here relating to MBS location estimators 1540 and MBS lo ⁇ tion tracks, and, the related programs hereinbelow are sufficientiy general so that these ideas and methods may be applied in a number of contexn related to determining the lo ⁇ tion of a device capable of movement and wherein the location of the device must be maintained in real time.
- the present ideas and methods may be used by a robot in a very cluttered environment (e.g, a warehouse), wherein the robot has access: (a) to a plurality of "robot lo ⁇ tion estimators" that may provide the robot with sporadic location information, and (b) to a deadreckoning location estimator.
- Each MBS 148 additionally, has a location display (denoted the MBS operator visual user interface 1558 in Fig.11) where area maps that may be displayed together with location da ⁇ .
- MS loration da ⁇ may be displayed on this display as a nested collection of areas, each smaller nested area being the most likely area within (any) encompassing area for lo ⁇ ting a target MS 140.
- the MBS controller algorithm below may be adapted to receive loration center 142 da ⁇ for displaying the locations of other MBSs 148 as well as target MSs 140.
- the MBS 148 may constrain any location estimates to streets on a street map using the MBS lo ⁇ tion snap to street module 1562.
- an estimated MBS location not on a street may be "snapped to" a nearest street location.
- a nearest street location determiner may use "normal" orientations of vehicles on streets as a constraint on the nearest street location.
- an MBS 148 is moving at typical rates of speed and acceleration, and without abrupt changes direction. For example, if the deadreckoning MBS location estimator 1544 indirates that the MBS 148 is moving in a northerly direction, then the street snapped to should be a north-south running street.
- the MBS location snap to street module 1562 may also be used to enhance ⁇ rget MS location estimates when, for example, it is known or suspected that the target MS 140 is in a vehicle and the vehicle is moving at typical rates of speed. Furthermore, the snap to street location module 1562 may also be used in enhancing the lo ⁇ tion of a target MS 140 by either the MBS 148 or by the location engine 139.
- the lo ⁇ tion estimator ⁇ or an additional module between the location estimator 1344 and the output gateway 1356 may utilize an embodiment of the snap to street location module 1562 to enhance the accuracy of ⁇ rget MS 140 location estimates that are known to be in vehicles. Note that this may be especially useful in lo ⁇ ting stolen vehicles that have embedded wireless location transceivers (MSs 140), wherein appropriate wireless signal measuremenn an be provided to the location center ⁇ .
- each MBS location estimate includes a "most likely MBS point location" within a "most likely area”.
- the "most likely MBS point location” is assumed herein to be the centroid of the "most likely area.”
- a nested series of "most likely areas” may be provided about a most likely MBS point location.
- each MBS location estimate is assumed to have a single "most likely area”.
- One skilled in the art will u ⁇ ders ⁇ nd how to provide such nested "most likely areas” from the description herein.
- each MBS location estimate also has a confidence associated therewith providing a measurement of the perceived accuracy of the MBS being in the "most likely area" of the location estimate.
- a (MBS) "location track” is an data structure (or object) having a queue of a predetermined length for main ⁇ ining a temporal (timestamp) ordering of "location track entries” such as the location track entries 1770a, 1770b, 1774a, 1774b, 1778a, 1778b, 1782a, 1782b, and 1786a (Fig.13), wherein each such MBS location track entry is an estimate of the lo ⁇ tion of the MBS at a particular corresponding time.
- MBS location track for storing MBS loration entries ob ⁇ ined from MBS location estimation information from each of the MBS baseline location estimators described above (i.e, a GPS location track 1750 for storing MBS lo ⁇ tion estimations ob ⁇ ined from the GPS location estimator 1540, a location center location track 1754 for storing MBS location estimations obtained from the lo ⁇ tio ⁇ estimator 1540 deriving in MBS lo ⁇ tion estimates from the location center 142, an LBS lo ⁇ tion track 1758 for storing MBS location estimations ob ⁇ ined from the loration estimator 1540 deriving in MBS lo ⁇ tion estimates from base s ⁇ tions 122 and/or 152, and a manual location track 1762 for MBS operator entered MBS locations).
- a GPS location track 1750 for storing MBS lo ⁇ tion estimations ob ⁇ ined from the GPS location estimator 1540
- location center location track 1754 for storing MBS location estimations obtained from the lo ⁇ tio ⁇ estimator 15
- lo ⁇ tion track 1766 there is one further lo ⁇ tion track, denoted the "current location track” 1766 whose location track entries may be derived from the entries in the other location tracks (described further hereinbelow).
- location track head that is the head of the queue for the location track.
- the lo ⁇ tion track head is the most recent (and presumably the most accurate) MBS lo ⁇ tion estimate residing in the location track.
- the time series of previous MBS location estimations (i.e, location track entries) in the location track will herein be denoted the "path for the loration track.”
- Such paths are typically the length of the lo ⁇ tion track queue containing the path. Note that the length of each such queue may be determined using at least the following considerations:
- each lo ⁇ tion track entry includes:
- a "derived location estimate" for the MBS that is derived using at least one of: (i) at least a most recent previous output from an MBS baseline location estimator 1540 (i.e, the output being an MBS location estimate); (ii) deadreckoning output information from the deadreckoning subsystem 1527. Further note that each output from an MBS location estimator has a "type” field that is used for identifying the MBS location estimator of the output. (b) an "earliest times ⁇ mp" providing the time/date when the earliest MBS location information upon which the derived location estimate for the MBS depends.
- a "deadreckoning distance” indicating the to ⁇ l dis ⁇ nce (e.g, wheel turns or odometer difference) since the most recently previous baseline entry for the corresponding MBS location estimator for the lo ⁇ tion track to which the location track entry is assigned.
- MBS location track entries there are two categories of MBS location track entries that may be inserted into a MBS location track: (a) “baseline” entries, wherein each such baseline entry includes (depending on the location track) a location estimate for the MBS
- each such entry includes an MBS location estimate that has been extrapolated from the (most recent) location track head for the location track (i.e, based on the track head whose "latest times ⁇ mp" immediately precedes the latest times ⁇ mp of the extrapolation entry).
- Each such extrapolation entry is computed by using da ⁇ from a related deadreckoning location change estimate outputfrom the deadreckoning MBS loration estimator 1544.
- Each such deadreckoning location change estimate includes measuremenn related to changes or deltas in the loration of the MBS 148.
- each extrapolation entry is determined using: (i) a baseline entry, and (ii) a set of one or more (i.e, all later occurring) deadreckoning location change estimates in increasing "latest times ⁇ mp" order. Note that for notationai convenience this set of one or more deadreckoning location change estimates will be denoted the
- baseline lo ⁇ tion tracks each having baseline entries exclusively from a single predetermined MBS baseline location estimator; and (b) a "current" MBS location track having entries that are computed or determined as "most likely” MBS location estimates from entries in the other MBS lo ⁇ tion tracks.
- the track heads of all loration tracks include MBS loration estimates that are for subs ⁇ ntiaiiy the same (latest) times ⁇ mp.
- the MBS loration information from each MBS baseline location estimator is inherently subs ⁇ ntiaiiy unpredictable and unsynchronized.
- the deadreckoning location change estimates from the deadreckoning MBS location estimator 1544 are the deadreckoning location change estimates from the deadreckoning MBS location estimator 1544 in that these estimates may reliably be ob ⁇ ined whenever there is a query from the location controller 1535 for the most recent estimate in the change of the location for the MBS 148. Consequently (referring to Fig.13), synchronization records 1790 (having at least a 1790b portion, and in some cases also having a 1790a portion) may be provided for updating each location track with a new MBS lo ⁇ tion estimate as a new track head.
- each synchronization record includes a deadreckoning location change estimate to be used in updating all but at most one of the location track heads with a new MBS location estimate by using a deadreckoning location change estimate in conjunction with each MBS location estimate from an MBS baseline location estimator, the location track heads may be synchronized according to times ⁇ mp. More precisely, for each MBS lo ⁇ tion estimate, E, from an MBS baseline location estimator, the present invention also subs ⁇ ntiaiiy simultaneously queries the deadreckoning MBS loration estimator for a corresponding most recent change in the lo ⁇ tion of the MBS 148.
- E and the retrieved MBS deadreckoning location change estimate, C have subs ⁇ ntiaiiy the same "latest times ⁇ mp".
- the location estimate E may be used to create a new baseline track head for the location track having the corresponding type for E, and C may be used to create a corresponding extrapolation entry as the head of each of the other location tracks.
- E and C will be hereinafter referred as "paired.”
- Such wireless location applications as were briefly described above in reference to the gateway 142 will now be described in further de ⁇ il. Hote that the following location related services are considered within the scope of the invention, and such services can, in general, be provided without use of a gateway 142, albeit, e.g, in a likely more restricted context wherein not all available wireless location estimating techniques are utilized, and/or by multiplying the number of interfaces to geolo ⁇ tion service providers (e.g, distinct wireless location interfaces are provided directly to each wireless location service provider utilized).
- hotels and other personal service providers such as auto ren l agencies, hotels, resorts and cruise ships may provide an inexpensive MS 140 that an be used substantially only for contacting: (i) the pe ⁇ onal service, (ii) emergency services, and/or (iii) receiving directions to return to the personal service.
- the MS 140 may be wirelessly lorated during operations (ii) and (iii) via wireless communi ⁇ tions between the MS 140 and a local commercial wireless service provider wherein a request to locate the MS 140 is provided to, e.g, the gateway 142, and the resulting MS location estimate is: provided to a public safety emergency center (e.g, E911) for dispatching emergency services, or provided to a mapping and routing system such as provided by Maplnfo or disclosed in the LeBlanc et. al. patent application filed Jan.22, 1999 and having U.S. Patent No.6,236,365 (which is fully incorporated herein by reference) so that the MS 140 user may be routed safely and expeditiously to a predetermined location of the personal service.
- da ⁇ representing the loration of the pe ⁇ onal service can be associated with an identification of the MS 140 so that MS activation for (iii) above results in one or more audio and/or visual presentations of directions for directing the user to return to the personal service.
- the MS 140 and the MS location providing wireless network may also provide the MS user with the ability to explicitly request to be substantially continuously tracked, wherein the MS tracked locations are stored for access by those having permission (e.g, the user, parenn and/or associates of the user). Additionally, the velocity and/or expected time of arrival at a predetermined destination may be derived from such tracking and may be provided to the user or his/her associates (e.g, employer, friends, and/or family). Further, note that this tracking and notification of information ob ⁇ ined therefrom maybe provided via a commercial telephony or Internet enabled mobile s ⁇ tion, or a mobile s ⁇ tion in operable communication with a short messaging service.
- the MS registered owner may provide permissions for those able to access such MS tracking information so that such information an be automatically provided to certain associates and/or provided on request to certain associates.
- the MS 140 and the MS loration providing wireless network may also allow the MS user to deactivate such MS tracking functionality.
- an MS user may activate such tracking for his/her MS 140 during working hours and deactivate such tracking during non-working hou ⁇ . Accordingly, an employer can then track employee's whereabouts during work hours, while the employee is able to re ⁇ in his/her lo ⁇ tion privacy when not working although the employer may be still able to con ⁇ ctthe employee in ⁇ se of an emergency during the employee's non-working time.
- this lo ⁇ tion capability and method of ob ⁇ ining location information about an MS user while assuring privacy at other times may be useful for appropriately monitoring in pe ⁇ onnel in the military, hospi ⁇ ls, transportation services (e.g, for couriers, bus and axis drivers), telecommunications personnel, emergency rescue and correctional institution personnel.
- this selective MS location capability may be performed in a number of ways.
- the MS 140 may activate and deactivate such tracking by dialing a predetermined number (e.g, by manually or speed dialing the number) for switching between activation of a process that periodically requests a wireless lo ⁇ tion of the MS 140 from, e.g, the location gateway 142.
- the resulting MS location information may be made available to other users at a predetermined phone number, Internet address or having sufficient validation information (e.g, a password).
- the MS location providing wireless network may automatically activate such MS tracking for predetermined times of the day and for predetermined days of the week. Note thatthis latter embodiment may be particularly useful for both tracking employees, e.g, at large construction sites, and, e.g, determining when each employee is at his/her work site.
- the MS location providing wireless network may provide da ⁇ base storage of times and days of the week for activation and deattivation of this selective MS tracking capability that is accessible via, e.g, a network service control pointio4 (or other telephony network control poinn as one skilled in the art will unders ⁇ nd), wherein triggers may be provided within the da ⁇ base for generating a network message (to, e.g, the gateway 142) requesting the commencement of tracking the MS 140 or the deattivation of such tracking.
- the resulting MS location information may be provided to an employer's tracking and payroll system so that the employer is able to determine the actual time an employee arrives at and leaves a work location site.
- an MS 140 and the MS location providing wireless network may provide the MS user with functionality to register certain lo ⁇ tions so that data representing such lo ⁇ tions an be easily accessed for use at a later time.
- the MS 140 user may be saying at a hotel in an unfamiliar area.
- the user can request, via his/her MS 140, that his/her location at the hotel be determined and registered so that it is available at a later time for routing the user back to the hotel.
- the user may have pe ⁇ onal lo ⁇ tion registrations of a plurality of locations in various cities and countries so that when traveling the user has wireless access to directions to preferred lo ⁇ tions such as his/her hotel, preferred restaurants, shopping areas, scenic areas, rendezvous poinn, theatres, athletic events, churches, entertainment establishments, locations of acquain ⁇ nces, etc.
- pe ⁇ onal location registration information may reside primarily on the user's subscriber network, but upon the MS user's request, his/her personal lo ⁇ tion registrations may be transmitted to another network from which the user is receiving wireless services as a roamer.
- any new lo ⁇ tion registrations may be dupli ⁇ ted in the user's personal registration of the user's subscriber network.
- an MS user may wish to retain such registered lorations only temporarily while the user is in a particular area; e.g, a predetermined network coverage area. Accordingly, the MS user may indicate (or such may be the default) that a new personal lo ⁇ tion registration be re ⁇ ined for a particular length of time, and/or until a lo ⁇ tion of the user is ounide the area to which such new location registrations appear to be applicable. However, prior to deleting any such registrations, the MS user may be queried to confirm such deletions.
- the MS user may be queried as whether to save the new Dallas, Texas lo ⁇ tion registrations permanently, for an particular length of time (e.g.30 days), or delete all or selected portions thereof.
- Other routing related applications of the present invention are for security (e.g, tracking how do I get back to my hotel safely), and, e.g, sight seeing guided tour where the is interactive depending on feedback from users
- Advertising may be directed to an MS 140 according to in location.
- MS 140 users do not respond well to unsolicited wireless advertisement whether location based or otherwise.
- certain advertisements may be viewed as more friendly.
- the user may be able to describe and receive (at his/her MS 140) audio and/or visual presen ⁇ tions of such producn or services that may satisfy such a user's request.
- a user may enter a request: "I need a Hawaiian shirt, who has such shins near here?"
- the present invention has advantages both for the MS user (as well as the wireline user), and for product and service providers that are nearby to the MS user.
- an MS user may be provided with (or request) a default set of advertisements for an area when the MS user ente ⁇ the area, registers with a hotel in the area, or makes a purchase in the area, and/or requesn information about a particular product or service in the area.
- an MS whose loration is being determined periodically may be monitored by an advertisement wizard such thatthis wizard may main ⁇ in a collection the MS user's preferences, and needs so that when the MS user comes near a business that ran satisfy such a preference or need, then an advertisement relating to the fulfillment of the preference or need may be presented to the MS user.
- this wizard may main ⁇ in a collection the MS user's preferences, and needs so that when the MS user comes near a business that ran satisfy such a preference or need, then an advertisement relating to the fulfillment of the preference or need may be presented to the MS user.
- this wizard may main ⁇ in a collection the MS user's preferences, and needs so that when the MS user comes near a business that ran satisfy such a preference or need, then an advertisement relating to the fulfillment of the preference or need may be presented to the MS user.
- Such potential advertising presen ⁇ tions be intelligently selected using as much information about the user as is available.
- MS user preferences and needs may be ordered according to importance.
- Such user preferences and needs may be categorized by temporal importance (i.e, must be satisfied within a particular time frame, e.g, immediately, today, or next month) and by situational importance wherein user 5 preferences and needs in this category are less time critical (e.g,. do not have to satisfied immediately, and/or within a specified time period), but if certain criteria are meet the user will consider satisfying such a preference or need.
- temporal importance i.e, must be satisfied within a particular time frame, e.g, immediately, today, or next month
- situational importance wherein user 5 preferences and needs in this category are less time critical (e.g,. do not have to satisfied immediately, and/or within a specified time period), but if certain criteria are meet the user will consider satisfying such a preference or need.
- finding a Chinese res ⁇ urantfor dinner may be in the temporal importance category while purchasing a bicycle and a new pair of athletic shoes may be ordered as listed here in the situational category.
- advertisements for Chinese restaurants may be provided to the user
- the advertising wizard may examine advertisements (or l o other available product inventories and/or services that are within a predetermined dis ⁇ nce of the route to the restaurant for determining whether there is product or service along the route that could potentially satisfy one of the user's preferences or needs from the situational importance category. If so, then the MS user be may provided with the option of examining such product or service information and registering the locations of user selected businesses providing such producn or services. Accordingly, the route to the restaurant may be modified to incorporate detours to one or more of these selected businesses.
- an MS user's situationally categorized preferences and needs may allow
- the wizard will attempt to present information (e.g, advertisements, coupons, discounn, product price and quality comparisons) related to producn and/or services that may satisfy the user's corresponding preference or
- the 20 need: (a) within the time frame designated by the MS user when identified as having a temporal constraint, and/or (b) consistent with situational criteria provided by the MS user (e.g, item on sale, item is less than a specified amount, within a predetermined traveling dis ⁇ nce and/or time) when identified as having a situational constraint.
- situational criteria e.g, item on sale, item is less than a specified amount, within a predetermined traveling dis ⁇ nce and/or time
- such information may be dependent on the geolocation of both the user and a merchants) having such producn and/or services.
- a proposed or expected user route e.g, a route to work, a trip route.
- items in the temporal category are ordered according how urgent must a preference or need must be 5 satisfied, while items in the situational category may be subs ⁇ ntiaiiy unordered and/or ordered according to desirableness (e.g, an MS user might want a motorcycle of a particular make and maximum price, want a new car more).
- desirableness e.g, an MS user might want a motorcycle of a particular make and maximum price, want a new car more.
- items in the situational category may be fulfilled subs ⁇ ntiaiiy serendipitous circumstances detected by the wizard, various orderings or no ordering may be used.
- the wizard may compare a new collection of merchant producn and/or services against the items on an MS user's temporal and situational lists, and at least alerting the MS user that there may be new information available about a user 0 desired service or product which is within a predetermined traveling time from where the user is.
- alerts may be visual (e.g, textual, or iconic) displays, or audio presen ⁇ tions using, e.g, synthesized speech (such as "Discounted motorcycles ahead three blocks at Cydes Cycles").
- advertising aspects of the present invention may be utilized by an intelligent electronic yellow pages which ran utilize the MS user's location (and/or anticipated locations; e.g, due to roadways being traversed) together with user preferences and needs (as well as other constraints) to both intelligently respond to user requesn as well as intelligently anticipate user preferences and needs.
- a block diagram showing the high level componenn of an electronic yellow pages according to this aspect of the present invention is shown in Fig.19.
- advertising is user driven in that the MS user is able to select advertising based on attributes such as: merchant proximity, traffic/parking conditions, the product/service desired, quality ratings, price, user merchant preferences, product/service availability, coupons and/or discounn.
- the MS user may be able to determine an ordering of advertisemenn presented based on, e.g, his/her selection inputs for categorizing such attributes. For example, the MS user may request advertisemenn athletic shoes be ordered according to the following values: (a) within 20 minutes travel time of the MS user's current lo ⁇ tion, (b) midrange in price, (c) currently in stock, and (d) no preferred merchants.
- the electronic yellow pages may have to make certain assumptions such if the MS user does not specify a time for being at the merchant, the electronic yellow pages may default the time to a range of times somewhat longer than the travel time thereby going on the assumption that MS user will likely be traveling to an advertised merchant relatively soon.
- the electronic yellow pages may also check stored da ⁇ on the merchant to assure that the MS user can access the merchant once the MS user arrives at the merchant's location (e.g, that the merchant is open for business). Accordingly, the MS user may dynamically, and in real time, vary such advertising selection parameters for thereby subs ⁇ ntiaiiy immediately changing the advertising being provided to the user's MS.
- the MS display may provide an area for entering an identification of a product/service name wherein the network determines a list of related or complementary products/services.
- an MS user desires to purchase a wedding gift, and knows that the couple to be wed are planning a trip to Australia, then upon the MS user providing input in response to activating a "related products/services" feature, and then inputting, e.g, "trip to Australia" (as well as any other voluntary information indicating that the purchase is for: a gift, for a wedding, and/or a price of less than $100.00), then the intelligent yellow pages may be able to respond with advertisemenn for related products/services such as portable electric power converter for pe ⁇ onal appliances that is available from a merchant local (and/or non-local) to the MS user. Moreover, such related products/services (and/or "suggestion") functionality may be interactive with the MS user.
- related products/services such as portable electric power converter for pe ⁇ onal appliances that is available from a merchant local (and/or non-local) to the MS user.
- the network may inquire as to the maximum travel time (or dis ⁇ nce) the MS user is willing to devote to finding a desired product/service, and/or the maximum travel time (or dis ⁇ nce) the MS user is willing to devote to visiting any one merchant.
- priorities may be provided by the MS user as to a presentation ordering of advertisemenn, wherein such ordering may be by: price
- parameter values may be for:: product/service quality ratings (e.g, display given to highest quality), price (low comparable price to high comparable price), travel time (maximum estimated time to get to merchant), 5 parking conditions.
- product/service quality ratings e.g, display given to highest quality
- price low comparable price to high comparable price
- travel time maximum estimated time to get to merchant
- Such electronic yellow pages may include the following functionality:
- Such displays may have a plurality of small advertisemenn that may be selected for hyperlinking to more derailed advertising information related to a product or service the MS user desires.
- this aspect of the present invention may, in one embodiment, provide displays (and/or corresponding audio information) that is similar to Internet page displays. However, such advertising may dynamically change with the MS user's
- the MS user may be able dynamically reprioritize the advertising displayed and/or change a proximity constraint so that different advertisemenn are displayed.
- the MS user may be able to request advertising information on a specified number of nearest merchann that provide a particular category of products or services. For example, an MS user may
- Electronic yellow pages center Assists both the use ⁇ and the merchann in providing more useful advertising for enhancing business transactions.
- the electronic yellow pages center may be a regional center within the carrier, or (as shown) an enterprise separate from the carrier.
- the center receives inputfrom users regarding preferences and needs which first received by the user interface,
- User interface Receives input from a user that validates the user via password, voice identification, or other biometric capability for identifying the user. Hote that the that the identification of user's communication device
- the user interface does one of: (a) validates the user thereby allowing user access to further electronic yellow page services, (b) requesn additional validation information from the user, or (c) invalidates the user and rejects access to electronic yellow pages. Hote that the user interface retrieves user identification information from the user profile da ⁇ base (described hereinbelow), and allows a validated user to add, delete, and/or modify such user identification information. l o c. User ad advisor-. Provides user interface and interattions with the user. Receives an identification/description of the user's communication device for determining an appropriate user communication technique.
- Hote that the user ad advisor may also query (any) user profile available (using the user's identity) for determining a preferred user communi ⁇ tion technique supported by the user's communi ⁇ tion device. For example, if the user's communication device supports visual presen ⁇ tions, then the user ad advisor defaults to visual presen ⁇ tions unless there are
- the user may request only audio ad presen ⁇ tions, or merely graphi ⁇ l pages without video.
- the user ad advisor may interactwith user solely via verbal interactions. Note that such purely verbal interactions may be preferable in some circumstances such as when the user ran not safely view a visual presentation; e.g, when driving. Further note that the user's communication device may sense when
- the user ad advisor includes a speech recognition unit (not shown) as well as a presentation manager (not shown) for outputting ads in a form compatible both with the functional capabilities of the user's communication device and with the user's interaction preference.
- the user ad advisor communicates: (a) with the user ad selection engine for selecting advertisemenn to be presented to the user, (b) with the user profile da ⁇ base for inputting thereto subs ⁇ ntiaiiy pe ⁇ istent user personal information that can be used by the user ad selection engine, and for retrieving user preferences such as media preference ⁇ for presentations of advertisemenn, and (c) with the user preference and needs satisfaction agenn for instantiating intelligent agents (e.g, da ⁇ base triggers, initiating merchant requesn
- intelligent agents e.g, da ⁇ base triggers, initiating merchant requesn
- the user ad advisor may also interact with a user for ob ⁇ ining feedback regarding: (a) whether the advertisemenn presented, the merchann represented, and/or the products/services offered are deemed appropriate by the user, and (b) the satisfaction with a merchant with which the user has interactions.
- feedback may be initiated and/or controlled subs ⁇ ntiaiiy by the user preference and needs satisfaction agent management system (described hereinbelow).
- User profile da ⁇ base A daobase management system for accessing and re ⁇ ining user identification information, 5 user pe ⁇ onal information, and identifi ⁇ tion of the user's communication device (e.g, make , model, and/or software versions) being used).
- the user profile da ⁇ base may con ⁇ in information about the user that is subs ⁇ ntiaiiy persistent; e.g, preferences for: language (e.g, English, Spanish, etc.), ad presentation media (e.g, spoken, textual, graphical, and/or video), maximum traveling time/distance for user preferences and needs of temporal importance (e.g, what is considered "near" to the user), user demographic information (e.g, purchasing l o history, income, residential address, age, sex, ethnicity, marital status, family statistics such as number of child and their ages), and merchant preferences/preclusions (e.g, user prefers one res ⁇ urant chain over another, or the user warmth no advertisemenn from a particular merchant).
- This module selects advertisemenn that are deemed appropriate to the user's preferences and needs. In particular, this module determines the ⁇ tegories and presentation order of advertisemenn to be
- the user ad selection engine uses a user's profile information (from the user profile da ⁇ base), a current user request (via the user ad advisor), and/or the user's current geolocation (via the interface to the location gateway 142).
- a user requesting the location of an Italian res ⁇ urant within Yi mile of the user's current loration, in a medium price range, and accepting out of town checks the user ad selection engine identifies the ad criteria within the user's request, and determines the advertising categories 20 (and/or values thereof) from which advertisemenn are desired.
- the advertising categories 20 and/or values thereof
- the user ad selection engine can suggest advertisement categories and/or values thereto to the user if requested to do so.
- an MS 140 appears to be traveling an extended dis ⁇ nce through a plurality of areas (as determined, e.g, by recent MS locations along an interstate that traverse a plurality of areas)
- each new area having a new collection of loration registrations may be provided.
- a new default set of local location registrations may become available to the user.
- the user may be notified that new temporary location registrations are available for the MS user to access if desired.
- such notification may be a color change on a video display indicating that new temporary registrations are available.
- the wizard may provide advertising for local businesses and services that are expected to better meet the MS user's ⁇ stes and needs.
- the MS user prefers fine 0 Italian food but does not want to travel more than 20 minutes by auto from his/her hotel to reach a res ⁇ urant, then advertisemenn for restaurants satisfying such criteria will become available to the user
- MS users may also remain anonymous to such wizards, wherein the Note, that by re ⁇ ining MS user preferences and needs, if permission is provided, e.g, for anonymously capturing such user information, this information could be provided to merchann.
- merchann can get an understanding of what nearby MS user's would like to purchase (and under what conditions, e.g, an electric fan for less than $ ⁇ o). Note such user's may be traveling through the area, or user's may live nearby. Accordingly, it is a feature of the present invention to provide merchant's with MS user preferences and needs according to whether the MS user is a passerby or lives nearby so that the merchant can better ⁇ rget his/her advertising.
- a single wizard may be used over the coverage area of a CMRS and the da ⁇ base of local businesses and services changes as the MS user travels from one location registration area to another. Moreover, such a wizard may determine the frequency and when requesn for MS locations are provided to the gateway 142. For example, such databases of local businesses and services may be coincident with LATA boundaries. Additionally, the wizard may ⁇ ke into account the direction and roadway the MS 140 is traveling so that, e.g, only businesses within a predetermined area and preferably in the direction of travel of the MS 140 are candidates to have advertising displayed to the MS user.
- the invention can used for sight seeing guided tours where the invention is interactive depending on feedback from users. Such interactivity being both verbal descriptions and directions to pointt of interest.
- the invention may provide Internet picture capture with real time voice capture and location information for sighneeing, and/or security.
Abstract
Description
Claims
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Also Published As
Publication number | Publication date |
---|---|
GB2384952A (en) | 2003-08-06 |
GB0230276D0 (en) | 2003-02-05 |
WO2001095642A3 (en) | 2002-06-06 |
WO2001095642B1 (en) | 2003-06-26 |
AU2001266674A1 (en) | 2001-12-17 |
GB2384952B (en) | 2005-02-09 |
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