Disclosed are techniques for wireless positioning. In an aspect, a first user equipment (UE) obtains one or more first radio frequency fingerprint (RFFP) measurements of one or more first downlink channels received at the first UE, one or more first sidelink channels received at the first UE, or both, and determines one or more locations of a target UE based on the one or more first RFFP measurements and a machine learning module, wherein the machine learning module is trained based on previously collected RFFP measurements of one or more downlink channels, RFFP measurements of one or more uplink channels, RFFP measurements of one or more sidelink channels, locations of one or more sidelink anchor UEs, locations of one or more base stations, or any combination thereof.

Systems and methods for indoor tracking via Wi-Fi fingerprinting and electromagnetic fingerprinting are provided and can include a gateway receiver device measuring a RSSI value of a signal transmitted by a Wi-Fi transmitter device, the gateway receiver device measuring an EMF value of an interference in an electromagnetic field created by the gateway receiver device that is caused by the Wi-Fi transmitter device, the gateway receiver device determining whether the RSSI value matches any of a plurality of Wi-Fi fingerprints associated with a monitored region and whether the EMF value matches any of a plurality of electromagnetic fingerprints associated with the monitored region, and responsive thereto, the gateway receiver device identifying that a location of the Wi-Fi transmitter device is within the monitored region.

An apparatus obtains results of measurements of a mobile device on radio signals transmitted by a radio transmitter at a site. The results include at least an identifier of the radio transmitter and an indication of a received signal strength of the radio signals. A plurality of radio transmitters are distributed at the site. The apparatus compares the received signal strength with a threshold. If the received signal strength exceeds the threshold, the apparatus causes a notification of a user of the mobile device, obtains an indication of a location based on a user input identifying a location on a map of the site, the map presented on a display of the mobile device, and causes storage of the identifier of the radio transmitter and the indication of the location as approximate location of the radio transmitter.

A mobile device is disclosed. The mobile device may receive one or more wireless local area network (WLAN) signals. The mobile device may determine Channel State Information (CSI) data from the one or more WLAN signals. The mobile device may determine one or more environmental characteristics associated with an environment of the mobile device based on the CSI data. The mobile device may send information indicative of the one or more environmental characteristics to a location server (LS), or determine a position of the mobile device based at least in part on the one or more environmental characteristics, or any combination thereof.

Systems and methods for reconstructing a trajectory from anonymized data are provided. In some aspects, a method includes receiving anonymized data corresponding to a trajectory of a user or object, and assembling, based on the anonymized data, a state-space model. The method also includes executing a prediction algorithm, based on the state-space model, to generate predicted data from the anonymized data, and reconstructing the trajectory of the user or object using the predicted data. The method further includes generating a report indicative of the trajectory.

An electronic device includes a receiver, a processor, and a communication unit. Via the communication unit from an external device, the processor receives altitude information on each of altitudes obtained at intervals of a first period, at intervals of a second period that is longer than the first period, and individually receives altitude information on an altitude obtained not at intervals of the first period. In response to receiving the altitude obtained not at intervals of the first period, the processor performs positioning at the receiving timing. Based on obtainment timings of the altitudes received at intervals of the second period and an obtainment timing of the altitude received individually, the processor correlates the altitudes received at intervals of the second period and the altitude received individually with positioning results of the positioning such that the obtainment timings correspond to positioning timings of the positioning results.

A method includes obtaining or causing obtaining a reference position of the at least one apparatus based on at least one reference tag located at a predefined position of a map represented by map data of at least part of a structure. The method also includes obtaining or causing obtaining identification information of at least one first wireless access point based on a radio signal of the at least one first wireless access point. The method further includes associating or causing associating a first position determined based on the reference position with at least one of: a position estimate determined based on the identification information of the at least one first wireless access point and a radiomap represented by radiomap data of at least part of a structure; of the identification information of the at least one first wireless access point. A corresponding apparatus is also disclosed.

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 position estimation apparatus estimates the position of a radio communication device that outputs a signal, where the apparatus includes a distance estimating section, a difference summing section, and a minimum difference candidate point determining section, where the distance estimating section estimates actual distances between wireless access points that receive the signal and the radio communication device as estimated distances based on the reception strength of the signal, where the difference summing section sums values based on differences between the distances between candidate points for the position of the radio communication device and the wireless access points and the estimated distances, where the minimum difference candidate point determining section determines a minimum difference candidate point, and where the position of the minimum difference candidate point is estimated as the position of the radio communication device.

A computer implemented method is disclosed for estimating a position of a vehicle. The method comprises obtaining dynamic state information for the vehicle at a first time in a time sequence the dynamic state information comprising position information for the vehicle. The method further comprises receiving, from the vehicle, communication network information for the vehicle at a second time in the time sequence that is after the first time, wherein the communication network information comprises a result of a measurement carried out by the vehicle on a signal exchanged with the communication network. The method further comprises using a trained ML model to estimate a position of the vehicle at the second time in the time sequence on the basis of the obtained dynamic state information and received communication network information.

Also disclosed are a communication network node, a training agent and associated methods.