It is provided a method for enabling determination of proximity of a mobile device (2a, 2b) to a selected proximity determiner (3a). The method comprises the steps of: determining a base set of proximity determiners (3b-e) whereby an enlarged set of proximity determiners is defined as the selected proximity determiner and the base set of proximity determiners; receiving beacon measurements of signal strength of other proximity determiners in the enlarged set of proximity determiners; generating a two-dimensional graph based on the beacon measurements; receiving respective device measurements indicating signal strength of a signal from the mobile device at each proximity determiner in the enlarged set of proximity determiners; finding an optimum in a space defined by the two-dimensional graph; and determining the most probable position of the mobile device in the graph based on the optimum.

A method for localizing a signal source which emits a signal, including determining a location-dependent bearing measurement of the signal source, receiving a type identification of the signal source, ascertaining a location-dependent residence probability (l.sub.threat({circumflex over (p)}), l.sub.shoot({circumflex over (p)}), l.sub.alt ({circumflex over (p)})) of the signal source depending on the received type identification of the signal source, superposing the location-dependent bearing measurement of the signal source with the location-dependent residence probability (l.sub.threat({circumflex over (p)}), l.sub.shoot({circumflex over (p)}), l.sub.alt({circumflex over (p)})).

A system may receive, from a network, an estimate of coordinates of a location of a potential interference source; determine, based in the estimate, whether the system is within a first threshold distance from the location; if the system is with the first threshold distance from the location, obtain real-time interference data from the network; determine, based on the real-time interference data, whether a source of interference exists near a first location that is within a second distance from a second location specified by the real-time interference data; and send a reply that indicates a result of the determination to the network.

Example embodiments relate to methods for estimating a location of at least one mobile network node and respective network. An example method for estimating a location of at least one mobile network node of a wireless communication network including the at least one mobile network node and at least two static network nodes includes performing initial range measurements between the at least two static network nodes in a pairwise manner. The method also includes determining an initial location estimate. Additionally, the method includes determining an estimate for corresponding noise samples. Further, the method includes estimating corresponding initial parameters of a Gaussian mixture noise model. In addition, the method includes determining a weighted sum of respective refined parameters of the Gaussian mixture noise model and the corresponding initial parameters of the Gaussian mixture noise model.

Systems and methods for spatial tracking using a hybrid signal are disclosed. A method for spatial tracking using a hybrid signal may include: receiving, from a peripheral unit and via an antenna array of a central unit, a signal that includes inertial measurement data from an inertial measurement unit (IMU) of the peripheral unit, and a constant tone extension (CTE); determining, based on the CTE, direction data for the peripheral unit; and determining, based on the direction data and the inertial measurement data, spatial tracking data for the peripheral unit.

The present invention relates to a method and apparatus for TDOA wireless positioning, has an effect of reducing positioning errors by reducing TDOA errors using destructive interference of multiple anchor nodes by dividing four or more anchor nodes into sets of three or more anchor nodes and by estimating a position of a tag node using TDOA of each set, and has an advantage of reducing the size and weight of the tag node since separate hardware is not required.

According to one embodiment, an electronic apparatus includes a processor configured to estimate positions of wireless devices communicating each other from a plurality of position candidates based on position candidate information indicating the position candidates of the wireless devices and communication information between the plurality of wireless devices located in any of the plurality of position candidates, and determine a first position among the position candidates according to a likelihood of the wireless devices estimated to be located in the position candidates.

An apparatus, method and computer program are disclosed. The apparatus may include circuitry configured for receiving from a target device, at a first time instance, a set of first measurement data associated with each of a plurality of base stations and determining a first position of the target device based on the received first sets of measurement data. The circuitry may also receive from the target device, at each of one or more subsequent time instances, a second set of measurement data associated with one, or each of a smaller number, of the base stations and determining, at each of the one or more subsequent time instances, a respective position of the target device based on the position determined at a previous time instance and the second set of measurement data.

Techniques are disclosed for predictive media streaming using microlocation. Microlocations of a mobile device can be determined by measuring one or more sensor values at one or more times, the one or more sensor values are determined from one or more signals emitted by a corresponding one or more signal sources. Streaming events can be stored at the mobile device. Each streaming event may include a destination device for playing media and a cluster location, the cluster location corresponding to sensor values that are spatially near each other. A selection of a media item is detected and one or more current sensor values are measured. A current cluster location can be identified using the one or more current sensor value. The current cluster location and the streaming events can identify a particular destination device for playing the selected media item.

A system and method for detection of an aerial drone in an environment includes a baseline of geo-mapped sensor data in a temporal and location indexed database formed by (i) using at least one sensor to receive signals from the environment and converting into digital signals for further processing; (ii) deriving time delays, object signatures, Doppler shifts, reflectivity, and/or optical characteristics from the received signals; (iii) geo-mapping the environment using GNSS and the sensor data; and (iv) logging sensor data over a time interval, for example 24 hours to 7 days. Live sensor data can be then be monitored and signature data can be derived by computing at least one parameter such as direction and signal strength. The live data is continuously or periodically compared to the baseline data to identify a variance, if any, which may be indicative of a detection event.