Systems, apparatuses, and methods for determining locations of wireless nodes in a network architecture are disclosed herein. In one example, a system for localization of nodes in a wireless network architecture, comprises a wireless node having a wireless device with one or more processing units and RF circuitry for transmitting and receiving communications in the wireless network architecture; and a plurality of wireless sensor nodes having a wireless device with a transmitter and a receiver to enable bi-directional communications with the wireless node in the wireless network architecture. One or more processing units of the wireless node are configured to execute instructions to determine ranging data including a set of possible ranges between the wireless node and the plurality of wireless sensor nodes having unknown locations, and to associate a set of relative locations within an environment of the wireless network architecture with the wireless node and the plurality of wireless sensor nodes.

Techniques are described for securely locating a user equipment (UE). Positioning measurements from the UE, which may be spoofed or not spoofed, are received by a location server, and used to determine a location uncertainty, which is used to determine whether the positioning measurements may be spoofed. The location uncertainty, for example, may be compared to an expected location uncertainty for positioning measurements that are not spoofed. If the location uncertainty is greater than the expected location uncertainty by more than a predetermined threshold, the positioning measurements may be spoofed. Positioning assistance data provided to the UE including information related to transmission times and transmission locations for positioning signals may be incomplete or inaccurate. Spoofed positioning measurements generated by a UE based on the incomplete or inaccurate information will include errors that produce a relatively large uncertainty compared to actual positioning measurements for which uncertainty would be smaller.

Disclosed are systems and techniques for managing an autonomous vehicle. In some aspects, an autonomous vehicle may obtain one or more radio frequency (RF) signals corresponding to a wireless device. In some cases, the autonomous vehicle may determine a location probability map associated with the wireless device based on the one or more RF signals. In some examples, the autonomous vehicle may adjust a behavior of the autonomous vehicle based on the location probability map associated with the wireless device.

A wireless device (12A) is configured to determine, for each of one or more links (14), one or more characteristics associated with wireless device positioning performance on the link. In some embodiments, the one or more characteristics include one or more of: geometric dilution of precision, GDOP, characteristics associated with the link; or line-of-sight, LOS, characteristics or non-LOS characteristics of the link. Regardless, the wireless device (12A) may also be configured to transmit control signaling (22) indicating the one or more characteristics determined for each of the one or more links (14). Based on this control signaling (22), a network node (16) may adapt positioning reference signal, PRS, configuration on at least one of the one or more links (14).

The present invention discloses a method and system for obtaining and tracking motions and gestures of a body part (e.g. a hand) of a user, by using antennas worn on the body (e.g. on a wrist band). The antennas may be near-field antennas which transmit and receive short-range electromagnetic fields. The electromagnetic fields may be modified by interaction with the body part, depending on the exact position of the body part. The modified electromagnetic field may be received by the antennas. The received signal may be processed, to provide additional spatial information (e.g. beamforming). The processed signal may be interpreted by pattern recognition (e.g. neural network, database table). The pattern recognition may be trained using labeled pair data (e.g. known hand positions and corresponding processed signals).

Disclosed are embodiments for determining a location of a wireless terminal. The wireless terminal measures signal strength of a plurality of wireless transmitters. Based on this information, a plurality of location probability surfaces are generated. Each location probability surface indicates a plurality of probabilities that the wireless terminal is in each of a corresponding plurality of geographic regions. These probability surfaces are then averaged to determine a composite location probability surface. A motion probability surface is also determined, which stores a plurality of probabilities indicating variations of motion of the wireless terminal. The composite location probability surface is then updated based on the motion probability surface. A location estimate of the wireless terminal is then determined based on the updated composite location probability surface.

The invention provides a method and system for tracking a position of one or more Wi-Fi devices of a plurality of Wi-Fi devices. For tracking the position of the one or more Wi-Fi devices, a Triggering Router triggers the one or more Wi-Fi devices to transmit one of a broadcast probe and a directed probe through broadcasting hidden SSID networks and common SSIDs that increase a probing tendency of the one or more Wi-Fi devices. The plurality of Wi-Fi sniffers, then, collect measurement data associated with the one or more Wi-Fi devices in response to detecting the broadcast probe transmission and the directed probe transmission. Thereafter, the position of the one or more Wi-Fi devices is estimated using an adaptive machine learning model based on an indoor model whose parameters are tuned based on radio frequency (RF) measurements from the plurality of Wi-Fi devices and the measurement data.

An apparatus obtains a set of radio data comprising signal strength related values for radio signals transmitted by a transmitter with an association of each signal strength related value with a representation of a geographical location. The apparatus applies a frequency transform to the obtained set of radio data to obtain transform coefficients, each transform coefficient comprising a transform index and an associated transform value. The apparatus selects a subset of transform indices having more significant transform values than the remaining transform indices and compresses the transform indices by encoding each transform index exploiting a probability of occurrence of an index value of a respective transform index. The same or another apparatus decodes the compressed transform indices again for use in position operations.

A method, an electronic device or customer-premise equipment, and a computer readable medium are disclosed for estimating a sound source. The method includes detecting, on an electronic device, voice data from a space; calculating, on the electronic device, an estimated voice source location from the detected voice data; detecting, on the electronic device, wireless location data from a positioning system within the space; calculating, on the electronic device, a probability of a user within one or more regions from the calculated estimated voice source location and the detected wireless location data, the one or more regions being regions of a plurality of regions within the space; and steering, from the electronic device, a microphone array for voice detection toward the one or more regions having the probability of the user within the one or more regions.

The location system includes two measurers apart from each other and configured to measure first and second variables in accordance with times of arrival of radio waves and first reception strengths, respectively; a memory configured to store first data associating a plurality of zones with first and second reference variables corresponding to times of arrivals of radio waves with respect to the two measurers for a case where the radio waves are transmitted from the plurality of zones, and second data associating the plurality of zones with first and second reference reception strengths with respect to the two measurers for the case where the radio waves are transmitted from the plurality of zones; and a processor configured to identify from among the plurality of zones a zone having a highest probability of including a position from where radio waves are transmitted.