Systems and methods provide for improving the accuracy of a location system. The location system can capture partial phase vector data from one or more access points (APs). The location system can capture associated data associated with the partial phase vector data across multiple dimensions, such as identity data of the APs and client devices generating the partial phase vector data and frequency band data, location data, a time and date, and other data associated with the partial phase vector data. The location system can determine correlation data across the multiple dimensions using the first partial phase vector data and the associated data. The location system can a cause of the partial phase vector data based on the correlation data. The location system can perform one or more remediation actions based on the cause of the partial phase vector data.

Presented herein are embodiments of signal detection and location finding directed to a “Signature Detector and Direction Finder” (SDDF) add-on module. The SDDF is an add-on module to any Signal Detection System (SDS) that detects, locates, and/or tracks any type(s) of Radio Frequency (RF) signals. Even though the presented embodiments can be used with any RF signal type, the preferred targets are Uncrewed Aerial Vehicles (UAV) or drones, and their controllers. A goal of the SDDF add-on module is to recognize the reported signal of interest and identify its direction. The machine-learning feature enables the system (i.e. SDDF add-on module with SDS) to be deployable in various environments with flexibility in choosing the antenna type(s). The Signature Detector component of the SDDF add-on module uniquely filters drone/controller signals, hence, more accurate direction estimation of the detected signal by SDDF add-on module.

An antenna device, a positioning system and a positioning method are provided. The positioning method includes: dispersedly arranging a plurality of receivers to form a target area, in which each of the receivers includes the antenna device; receiving a wireless signal from the target area through the antenna device, and generating a difference signal strength and a sum signal strength; calculating, for each of the receivers, a sum-difference ratio between the difference signal strength and the sum signal strength, and estimating a corresponding one of estimated incident angles according to the sum-difference ratio and a comparison table; executing, in response to obtaining the estimated incident angles corresponding to the receivers, a positioning algorithm according to the estimated incident angles, so as to generate a plurality of possible positions; and executing an optimization algorithm to calculate a best estimated position of the possible positions.

A sensor is configured to receive connection information from a portable device via a communication gateway in a vehicle and to communicate with a portable device using impulse radio (IR) ultra-wide band (UWB) communication based on the connection information. A location of the portable device is determined based on ranging using IR UWB communication.

A sensor is configured to receive connection information from a portable device via a communication gateway in a vehicle and to communicate with a portable device using impulse radio (IR) ultra-wide band (UWB) communication based on the connection information. A location of the portable device is determined based on ranging using IR UWB communication.

A tracking system can provide configuration instructions to an electronic device based on user presence. The tracking system can determine a user's location relative to a geographic boundary surrounding a geographic area associated with the user. Depending on the user's location, the tracking system may send instructions to configure an electronic device to send a notification or change the operating mode of the electronic device in response to the user's presence. The electronic device may be a scanning device that is configured to have a higher or lower scanning frequency, depending on the presence or absence of the user relative to the scanning device.

A tracking system can provide configuration instructions to an electronic device based on user presence. The tracking system can determine a user's location relative to a geographic boundary surrounding a geographic area associated with the user. Depending on the user's location, the tracking system may send instructions to configure an electronic device to send a notification or change the operating mode of the electronic device in response to the user's presence. The electronic device may be a scanning device that is configured to have a higher or lower scanning frequency, depending on the presence or absence of the user relative to the scanning device.

A system provides a way to determine angle of bearing to a target receiver/transmitter relative to plural beacon stations with rotating directional radiation patterns. The target is “cooperative” in that it transmits a “report” message when the target receives maximum signal strength from a beacon station. Triangulation from multiple beacon transmitter sites can be used to determine the target's position.

A system provides a way to determine angle of bearing to a target receiver/transmitter relative to plural beacon stations with rotating directional radiation patterns. The target is “cooperative” in that it transmits a “report” message when the target receives maximum signal strength from a beacon station. Triangulation from multiple beacon transmitter sites can be used to determine the target's position.

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.