Abstract:
A process and machine for estimating the location of a wireless terminal is disclosed. The illustrative embodiment of the present invention is based on the observation that the signal strength of a signal from a transmitter is different at some locations, and, therefore, the location of a wireless terminal can be estimated by comparing the signal strength it currently observes against a map or database that correlates locations to signal strengths. In accordance with a first example, if a particular radio station is known to be received well at a first location and poorly at a second location, and a given wireless terminal at an unknown location is receiving the radio station poorly, it is more likely that the wireless terminal is at the second location than it is at the first location.
Abstract:
A method of using a non-GPS-derived technique to estimate the location of an Assisted-GPS-enabled wireless terminal for the purposes of generating location-specific assistance data for the wireless terminal is disclosed. The wireless terminal then uses the assistance data to acquire and process one or more GPS signals and to derive information that is probative of the wireless terminal's location. The GPS-derived location information is then combined with non-GPS-derived location to form an estimate of the location of the wireless terminal that is better than can be derived from either alone. This combination of GPS-derived and non-GPS techniques is particularly useful when the wireless terminal can only acquire one or two GPS signals because it is not possible to determine the location of the wireless terminal with only two GPS signals alone.
Abstract:
It is an object of the present invention to perform positioning at favorable positioning precision and in a favorable positioning time, according to whether a receiver is indoors or outdoors. A positioning server 10 comprises a reception state information acquisition component 12 that acquires reception state information indicating the reception state of a radio wave at a cellular terminal 20, a base station positioning calculator 13 that estimates the position of the cellular terminal 20 on the basis of the reception state information, an end decision component 14 that decides whether or not to end the position estimation on the basis of a specific end condition, and, if it is decided not to end, estimates the position of the cellular terminal 20 on the basis of new reception state information, an indoor/outdoor determination component 15 that determines whether the cellular terminal 20 is indoors or outdoors on the basis of the reception state information, and an end condition determination component 16 that determines the specific end condition on the basis of a result of determination by the indoor/outdoor determination component 15.
Abstract:
A method of using a non-GPS-derived technique to estimate the location of an Assisted-GPS-enabled wireless terminal for the purposes of generating location-specific assistance data for the wireless terminal is disclosed. The wireless terminal then uses the assistance data to acquire and process one or more GPS signals and to derive information that is probative of the wireless terminal's location. The GPS-derived location information is then combined with non-GPS-derived location to form an estimate of the location of the wireless terminal that is better than can be derived from either alone. This combination of GPS-derived and non-GPS techniques is particularly useful when the wireless terminal can only acquire one or two GPS signals because it is not possible to determine the location of the wireless terminal with only two GPS signals alone.
Abstract:
A location engine uses the empirical measurements made by a scouting wireless terminal (i) to discover the existence of a reference radio within a geographic region; (ii) to generate an estimate of the location of the newly-discovered reference radio, and (iii) to generate an estimate of the transmission power of the downlink control channel radio signal transmitted by the newly-discovered reference radio. The location engine then uses: (i) the estimate of the location of the newly-discovered reference radio, and (ii) the estimate of the transmission power of the downlink control channel radio signal transmitted by the newly-discovered reference radio, and (iii) measurements, made by a user wireless terminal, of the power of each of the downlink control channel radio signals transmitted by each of the reference radios to generate an estimate of the location of the user wireless terminal.
Abstract:
A method for estimating the pressure measurement bias of a barometric sensor in a wireless terminal. A location engine using the method generates an enhanced estimate of the measurement bias. The location engine generates the enhanced estimate based in part on relatively coarse estimates of the elevation of the wireless terminal. The coarse estimates are used to generate instantaneous estimates of measurement bias and bias uncertainty. As needed, the location engine adjusts the instantaneous estimate of bias uncertainty, in order to reflect an instantaneous estimate of measurement bias that is recognized as being in error. The adjustment is based on what is expected as a probable measurement bias value for the particular wireless terminal. Once the location engine generates the enhanced estimate of measurement bias, it can generate improved estimates of elevation of the wireless terminal.
Abstract:
A location engine uses the empirical measurements made by a scouting wireless terminal (i) to discover the existence of a reference radio within a geographic region; (ii) to generate an estimate of the location of the newly-discovered reference radio, and (iii) to generate an estimate of the transmission power of the downlink control channel radio signal transmitted by the newly-discovered reference radio. The location engine then uses: (i) the estimate of the location of the newly-discovered reference radio, and (ii) the estimate of the transmission power of the downlink control channel radio signal transmitted by the newly-discovered reference radio, and (iii) measurements, made by a user wireless terminal, of the power of each of the downlink control channel radio signals transmitted by each of the reference radios to generate an estimate of the location of the user wireless terminal.
Abstract:
A method for performing contact tracing. An analysis system performing the method receives geo-temporal data comprising location data points for various wireless terminals, including the wireless terminal being used by a person diagnosed as having a specified disease and the wireless terminals of people who possibly have come in contact with the infected person. Based on filtering the geo-temporal data, the analysis system generates relatively-condensed mobility profiles that are representative of each person's locations and movements, and analyzes the mobility profiles. Through careful selections of various parameters based on the disease that is being analyzed, the mobility profiles are used instead of the relatively large amounts of geo-temporal data, to represent users of wireless terminals and to determine their interactions in regard to disease transmission.
Abstract:
A method for estimating the location of a wireless terminal at an unknown location, such as within a building. A location engine using the disclosed method receives and uses samples of barometric pressure measured by the wireless terminal to generate a characterization of a pressure wave in the vicinity of the wireless terminal. The location engine generates an estimate of the location of the wireless terminal based on the characterization of the pressure wave and, in some cases, the location of the source of the pressure wave, such as a building's door that is opening or closing. The location engine also bases the estimate of the wireless terminal's location on a propagation characteristic of the pressure wave, such as its speed of propagation.
Abstract:
A system and method according to the principles of the invention identifies mobile phone aliases. The system processes mobile location data and call event data to generate mobility profiles. The profiles indicate a mobile's geographic zone history over a specified time. To produce a mobility profile, the system aggregates location data into zones and associates the zones with times of day, week or month. Particular zones for different mobiles can be compared according to weighting algorithms to provide data indicating whether the mobiles belong to the same user.