An architecture is provided for cooperative target tracking and signal propagation learning using mobile sensors. A method can comprise as a function of sensing data representative of a location of a target device at a first defined moment and model data relating to a motion model representing a probability density function, determining, by a system comprising a processor, a group of locations for the target device at a second defined time point, wherein the probability density function facilitates determining, based on the location of the target device at the first defined moment, a current location of the target device at a third defined moment; and as a function of the group of locations, generating, by the system, a data structure representing a matrix of received signal strength values; and identifying, by the system, a location of the group of locations for the target device at the third defined moment based on the data structure.

Examples described herein provide automatic location of access points by a computing device. Examples may include receiving, by the computing device from each AP in a subset of a plurality of APs, a Global Navigation Satellite System (GNSS) signal measurement, and based on each received GNSS signal measurement, constraining, by the computing device, the map of relative AP locations by at least one translational degree of freedom or one rotational degree of freedom. Examples may include resolving, by the computing device, locations of the plurality of APs in the map of relative AP locations.

Methods for geolocation utilizing electronic distance measurement equipment. The methods select a small subset of available data that is most trustworthy, and then mathematically treats the subset of data (preferably bilateration or trilateration) to compute one or more new measured position candidates. One measured position candidate may be chosen among the measure position candidates based on confidence metrics, relative position geometry, and the comparison with history-based predicted position and its respective confidence metric. In a case where no measured position candidates of sufficient confidence are available, the predicted position is taken as the new position.

Methods, systems, and devices for wireless communications are described. In a wireless communications system, one or more user equipments (UEs) may implement distance-limited sidelink-based ranging techniques. An initiating UE may transmit one or more positioning reference signal (PRS) request messages to one or more target UEs via a sidelink channel. In some cases, the initiating UE may receive one or more response messages from at least one target UE that is located within a threshold distance from the initiating UE. In some examples, based on receiving the one or more response messages, the initiating UE may transmit PRSs to each target UE that transmitted a response message.

A method and apparatus for determining a device pointed to by a UE is provided. The method includes determining UE pointing information based on spatial information of UWB devices; and determining a target non-UWB device pointed to by the UE based on the UE pointing information and spatial information of at least one non-UWB device. The disclosure determines a target non-UWB device pointed to by the UE in the UWB environment based on spatial perception capability of UWB and improve the user experience of UWB pointing operations.

A method for controlling the position of an updating agent in a decentralised multi-agent system, the method comprising: identifying a first neighbouring agent within a communicative range of the updating agent; estimating a first distance to the first neighbouring agent and a first direction to the first neighbouring agent; determining a movement direction based on the first direction to the first neighbouring agent; and determining a movement magnitude based on an activation function, the first distance to the first neighbouring agent, and a desired reference distance. The activation function is configured such that the greater the difference between the first distance to the neighbouring agent and the desired reference difference, the larger the movement magnitude. The method further comprises moving the updating agent based on the movement direction and the movement magnitude.

A sensing system including multiple sensor node devices and an analysis device, wherein: each of the multiple sensor node devices has a sensor that measures a measurement target and acquires data values, a learning unit that, based on the data values, learns a model used to estimate the data values at an installation position of the sensor, and a communication unit that transmits learning result data indicating a learning result from the learning unit; and the analysis device has a spatial analysis unit that estimates a spatial distribution of the data values based on the learning result data from each of the multiple sensor node devices and the installation positions of the respective sensor node devices.

A system may be configured to identify from among a plurality of access points in an area in communication with a network, a first access point associated with the area. In addition the system may also be configured to determine first location-related data for the first access point. Determining second location-related data for a second access point of the plurality of access points, the second access point being interior to the first access point within the network includes exchanging ranging data indicative of a first relative distance between the first access point and the second access point, the ranging data based at least in part on ranging message exchange measurements, and communicating the first location-related data from the first access point to the second access point.

Proposed is a method of determining a location for swarm flight using UWB, the method including: computing a reference location from GPS information in a case where the location is measured; sending out a pulling signal, preset according to a two-way ranging format, according to slave ranging scheduling corresponding to each formation, and receiving a pushing signal from a neighboring flight vehicle and performing ranging; computing a relative location in the formation on a master-slave basis from a ranged pull-push relationship using TWR time information, and computing the relative location in the formation on a slave-slave basis using a received signal strength indicator and time of arrival; generating a fingerprint map in a manner that varies with each formation, using all the computed relative locations in the formation on the master-slave basis; and computing the location of the swarm flight vehicle using the generated fingerprint map.

Localization systems and methods for transmitting timestampable localization signals from anchors according to one or more transmission schedules. The transmission schedules may be generated and updated to achieve desired positioning performance. For example, one or more anchors may transmit localization signals at a different rate than other anchors, the anchor transmission order can be changed, and the signals can partially overlap. In addition, different transmission parameters may be used to transmit two localization signals at the same time without interference. A self-localizing apparatus is able to receive the localization signals and determine its position. The self-localizing apparatus may have a configurable receiver that can select to receive one of multiple available localization signals. The self-localizing apparatuses may have a pair of receivers able to receive two localization signals at the same time. A bridge anchor may be provided to enable a self-localizing apparatus to seamlessly transition between two localization systems.