A computer-implemented method for combined indoor and outdoor tracking using a tracking device is disclosed. In at least one embodiment of the method, a fingerprint of radio signals is generated by the device at a location to be determined. The location of the device is determined by applying trained functions to the fingerprint wherein the trained functions have been end-to-end trained using a plurality of fingerprints generated at known locations. Environmental sensor data may be used to predict a lifetime of a component tracked by the tracking device.

A wireless communication method for use in a user terminal comprises receiving, from a network entity or a first wireless network node, prior channel information related to at least one channel between each of at least one wireless terminal and each of at least one second wireless network node, and determining at least one characteristic of the user terminal based on the prior channel information.

Mobile equipment including a geo-localization device arranged to determine a current position for the mobile equipment in a space to be mapped; a communication device arranged to communicate with access points of a local network implemented in the space to be mapped; a control component arranged: to control each access point selectively and in independent manner via the communication device so as to cause said access point to transmit a reference signal; to use the reference signals received by the communication device to evaluate respective qualities for the connections between each of the access points and the mobile equipment in the current position.

Disclosed is an approach to enable radio map download for Global Navigation Satellite System (GNSS)-denied areas. In particular, processor(s) (e.g., of positioning server(s)) could identify GNSS-denied area(s) in an initial radio map, the GNSS-denied area(s) being (i) one or more areas in which at least one GNSS signal is or was unavailable and (ii) a subset of a plurality of areas represented by the initial radio map. Subsequently, the processor(s) could generate a partial radio map representing radio data only for the GNSS-denied area(s) identified in the initial radio map, and could then transmit the partial radio map to a mobile device for storage at the mobile device. In this way, the mobile device could optimize resource usage and perform radio-based position estimations at least in the GNSS-denied area(s) that were identified.

A system for determining the location of a wireless device is described, the system includes a map, a fixed beacon, a fixed sensor and a server component. The server component receives a beacon identifier and a beacon signal strength from a wireless device. A sensor is located on the map. The fixed sensor receives the beacon identifier and the sensor captures a measured sensor beacon signal strength. The sensor is communicatively coupled to the server component. The server component receives the beacon identifier and the measured sensor beacon signal strength from the fixed sensor. The server component uses the beacon identifier and the beacon signal strength communicated by the wireless device and the sensor beacon signal strength and the beacon identifier received by the sensor to determine the location of the wireless device.

First information corresponding to a radio signal received at a first sensing device from a candidate location is obtained. Second information corresponding to a radio signal received at a second sensing device from the candidate location is obtained. A first relationship between the first sensing device and the candidate location and a second relationship between the second sensing device and the candidate location are determined. A first inverse and a second inverse of respectively the first and second relationships are obtained. A first estimate of the radio signal at the first sensing device is determined from the first information and the first inverse. A second estimate of the radio signal at the second sensing device is determined from the second information and the second inverse. Energy emitted from the candidate location is measured based on the first estimate and the second estimate.

A computer-implemented method for precision hyperbolic location fingerprinting, the method comprising, at a computing system, the steps of: (a) receiving measured RSSI values associated with a plurality of fixedly-positioned sensor devices, wherein the plurality of fixedly-positioned sensor devices are stationary in known locations in a 2D environment and caused to transit radio signals to each other and measure characteristics of the received radio signals; (b) generating a raw RSSI fingerprint for each sensor device based on the measured RSSI values; (c) generating a log-ratio RSSI fingerprint between a pair of sensor devices; (d) normalizing the raw RSSI fingerprint and normalizing the log-ratio RSSI fingerprint; (e) combining the raw RSSI fingerprint and the log-ratio RSSI fingerprint to form a fusion RSSI fingerprint; and (f) repeating steps (a) to (e) at predetermined intervals to enhance prediction accuracy of regional fingerprints within the environment.

A system and methods for estimating the location of a mobile device are disclosed. In accordance with one embodiment, a mobile device located within a first corridor of a building receives (1) a first wireless electromagnetic signal and a first ultrasound signal from a first beacon located in the first corridor, (2) a second wireless electromagnetic signal and a second ultrasound signal from a second beacon located in the first corridor, and (3) a third wireless electromagnetic signal from a third beacon located in a second corridor of the building. The first wireless electromagnetic signal, the first ultrasound signal, the second wireless electromagnetic signal, and the second ultrasound signal are used to estimate a location of the mobile device.

Methods and systems are provided for determining a location of a device. The methods can include receiving information associated with a device, which can include one or more radio frequency (RF) signal strength values associated with communication between the device and at least one antenna element of an antenna array. The methods can also include, determining, based at least partly on the information associated with the device, a location for the device.

A system and method for classifying a type of interaction between a human user and a mobile communication device within a defined volume, based on multiple sensors. The method may include: determining a position of the mobile communication device relative to a frame of reference of the defined volume, based on: angle of arrival, time of flight, or received intensity of radio frequency (RF) signals transmitted by the mobile communication device and received by a phone location unit located within the defined volume configured to wirelessly communicate with the mobile communication device; obtaining at least one sensor measurement related to the mobile communication device from various non-RF sensors; repeating the obtaining, to yield a time series of sensor readings; and using a computer processor to classify the type of interaction into one of many predefined types of interactions, based on the position and the time series of sensor readings.