Systems and methods for determining user equipment (UE) locations within a wireless network using reference signals of the wireless network are described. The disclosed systems and methods utilize a plurality of in-phase and quadrature (I/Q) samples generated from signals provided by receive channels associated with two or more antennas of the wireless system. Based on received reference signal parameters the reference signal within the signals from each receive channel among the receive channels is identified. Based on the identified reference signal from each receive channel, an angle of arrival between a baseline of the two or more antennas and incident energy from the UE to the two or more antennas is determined. That angle of arrival is then used to calculate the location of the UE. The angle of arrival may be a horizontal angle of arrival and/or a vertical angle of arrival

Example implementations may relate to making a determination of whether a mobile device is positioned indoors or outdoors. More specifically, processor(s) may detect that the mobile device is connected to a particular access point and may determine that the particular access point is stationary rather than moving. In response to determining that the particular access point is stationary, the processor(s) may determine (i) a distance between the mobile device and the particular access point, and/or (ii) a connection duration representing a length of time that the mobile device has been connected to the particular access point. Based at least on the determined distance and/or on the determined connection duration, the processor(s) may then make the determination of whether the mobile device is positioned indoors or outdoors.

A communication system that includes a plurality of radio points is disclosed. Each radio point is configured to exchange radio frequency (RF) signals with a wireless device that transmits a Sounding Reference Signal (SRS) from a first physical location in a site; and extract at least one SRS metric from the SRS. The communication system also includes a baseband controller communicatively coupled to the plurality of radio points. The baseband controller is configured to determine a signature vector based on the at least one SRS metric from each of the plurality of radio points. The communication system also includes a machine learning computing system communicatively coupled to the baseband controller. The machine learning computing system is configured to use a machine learning model to determine location data for the first physical location of the wireless device based on the signature vector.

A method includes retrieving a map of a 3D geometry of an environment the map including a plurality of non-spatial attribute values each corresponding to one of a plurality of non-spatial attributes and indicative of a plurality of non-spatial sensor readings acquired throughout the environment, receiving a plurality of sensor readings from a device within the environment wherein each of the sensor readings corresponds to at least one of the non-spatial attributes and matching the plurality of received sensor readings to at least one location in the map to produce a determined sensor location.

A method, computer program, and computer system of a base station is provided for determining a location of a mobile device by receiving data from a mobile device associated with a location of the mobile device and generating a world model database corresponding to a physical location of the base station. The received data is constrained based on the generated world model database, and an updated location of the mobile device is determined based on the constrained data.

A 5G-signal-based DOA fingerprint-based positioning method includes the following steps: dividing an initial area into a number of micro-cells, and estimating angle information of reference points in the divided micro-cells; storing the angle information of the reference point of each micro-cell and position information of the each micro-cell in a fingerprint database, and updating the angle information in the fingerprint database at regular intervals; wherein when there is a target in the initial area, estimating angle information of the target; matching the angle information of the target with the angle information in the fingerprint database to determine a micro-cell where the target is located to obtain position information of the target, so as to locate the target.

A method is disclosed, performed by at least a first apparatus, for managing at least a second apparatus, the second apparatus being a sensor and/or actuator device or a part thereof, the method comprising: obtaining identifier information of the second apparatus and obtaining positioning information associated with the identifier information and indicative of a position of the second apparatus; determining updated positioning information of the second apparatus at least based on an obtained radio measurement taken by the second apparatus; and at least based on the updated positioning information of the second apparatus, determining whether the second apparatus has been relocated and/or updating the positioning information associated with the identifier information of the second apparatus.

A data processing method includes obtaining positioning data collected during positioning, obtaining a fingerprint set from a location database based on the positioning data, where the fingerprint set includes at least one fingerprint, and each fingerprint in the fingerprint set includes at least one positioning media access control (MAC) address, determining, for each fingerprint in the fingerprint set, a matching degree between the fingerprint and the positioning data based on a second signal strength and a first signal strength of each positioning MAC address in the fingerprint, and determining that an access point (AP) included in the positioning data moves when each of matching degrees of all fingerprints in the fingerprint set is less than a first threshold.

Embodiments are disclosed for a method that may include accessing events in a field-searchable data store. The events may include raw machine data associated with a timestamp. The raw machine data may represent interactions between a mobile device and one or more network devices at a locale. The method may further include determining, based on the interactions, one or more geographic positions of the mobile device, and calculating a metric for the locale using the geographic positions.

A computer implemented method for determining an initial ego-pose for initialization of self-localization comprises the following steps carried out by computer hardware components: providing a plurality of particles in a map; grouping the particles in a plurality of clusters; performing particle filtering individually for each of the clusters; and determining an initial ego-pose based on the particle filtering.