Techniques for enabling a cross-link interference (CLI) based uplink (UL) angle-of-arrival (AoA) estimations are disclosed. A victim user equipment (UE) may be configured with CLI resources to measure CLIs from one or more aggressor UEs. The victim UE may take the CLI opportunities also to estimate the AoAs of the UL signals from the aggressor UEs. In this way, UE's location estimation may be enhanced.

A method and a system detect damage caused to a parked vehicle and identify the originator of the damage.

The present invention relates to a method for determining a position of a first device with respect to a second device. According to the method, control data indicative of a receive property of at least one signal received from the first device (110) by a second device (121-124) using a plurality of receiver chains (210-215) is established. At least one receive characteristic of the plurality of receiver chains (210-215) differs for at least two receiver chains of the plurality of receiver chains (210-215). Based on the control data, positioning information for the first device (110) is determined.

The present invention relates to a method for determining a position of a first device with respect to a second device. According to the method, control data indicative of a receive property of at least one signal received from the first device (110) by a second device (121-124) using a plurality of receiver chains (210-215) is established. At least one receive characteristic of the plurality of receiver chains (210-215) differs for at least two receiver chains of the plurality of receiver chains (210-215). Based on the control data, positioning information for the first device (110) is determined.

A method is provided for estimating a signal's angle of arrival (AOA) in a communications system. Starting values for each of a horizontal AOA and a vertical AOA are estimated. The estimated vertical AOA starting value is used to select a horizontal PDOA trace of horizontal PDOA calibration data. The selected horizontal PDOA trace is interpolated to determine a best horizontal AOA estimate for a current iteration. The estimated horizontal AOA starting value is used to select a vertical PDOA trace of vertical PDOA calibration data. The selected vertical PDOA trace is interpolated to determine a best vertical AOA estimate for the current iteration. After each iteration, determining if a maximum number of iterations has been reached or if the best horizontal or vertical AOA estimate has not changed by a predetermined amount. When one of these is true, the best horizontal and vertical AOA estimates are used.

Techniques for determining a location of a client device using recursive phase vector subspace estimation are described. One technique includes receiving a plurality of angle-of-arrival (AoA) measurements from a plurality of access points (APs). Each AoA measurement includes a plurality of entries for phase values measured from a signal received from a client device at the plurality of APs. At least one AoA measurement of the plurality of AoA measurements that includes at least one of: (i) one or more entries with missing phase values and (ii) one or more entries with erroneous phase values is identified, based on a recursive phase estimation. The plurality of AoA measurements are updated based on the identified at least one AoA measurement. The location of the client device is determined, based on the updated plurality of AoA measurements.

An electronic device includes an indoor positioner and a positioning engine server. The indoor positioner has an antenna array including a plurality of antenna units. The indoor positioner divides the antenna units into multiple antenna unit groups, receives a wireless signal from user equipment at each time point via the antenna unit groups, and calculates a plurality of angles of arrival (AOA) corresponding to the antenna unit groups at each time point. The positioning engine server receives and stores the angles of arrival corresponding to the antenna unit groups at each time point, and filters the angles of arrival according to the angle sizes of the angles of arrival corresponding to the antenna unit groups at each time point stored in an observation period.

An electronic device includes an indoor positioner and a positioning engine server. The indoor positioner has an antenna array including a plurality of antenna units. The indoor positioner divides the antenna units into multiple antenna unit groups, receives a wireless signal from user equipment at each time point via the antenna unit groups, and calculates a plurality of angles of arrival (AOA) corresponding to the antenna unit groups at each time point. The positioning engine server receives and stores the angles of arrival corresponding to the antenna unit groups at each time point, and filters the angles of arrival according to the angle sizes of the angles of arrival corresponding to the antenna unit groups at each time point stored in an observation period.

A system and method for classifying a type of calibration or maintenance event of a phone location unit (PLU) within a defined volume, based on at least one sensor, the method comprising: determining a position of the at least one mobile communication device relative to a frame of reference of the defined volume; obtaining at least one sensor measurement related to the at least one mobile communication device, from a sensor located on at least one of: the at least one mobile communication device, within the defined volume, or outside of the defined volume; and using a computer processor to classify the type of calibration or maintenance event of the PLU, into one of a plurality of predefined types of calibration or maintenance event, based on the position and the at least one sensor measurement.

A system and method for classifying a mode of operation of a mobile communication device within a defined volume, based on multiple sensors are provided herein. The method may include the following steps: determining a position of the mobile communication device relative to a frame of reference of the defined volume, based on any of: 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 at least one mobile communication device; obtaining at least one sensor measurement related to the mobile communication device from various non-RF sensors; and using a computer processor to classify the mobile communication device into one of many predefined modes of operation of the mobile communication device, based on the position and the sensor readings.