A method for geolocating a terminal of a wireless communication system, based on a learning method making it possible to estimate the geographical position of a terminal using both a radio signature corresponding to a set of values representative of the quality of radio links existing between the terminal located at the sought position and a plurality of base stations of the wireless communication system, as well as a reference data set associating radio signatures with known geographical positions. To limit the complexity of the learning algorithm and to make it resistant to topology changes of the access network, each radio signature contains a selection of N values among the set of measured values, as well as the geographical positions of the corresponding base stations.

A method is provided that includes collecting radio fingerprints with each fingerprint including a radio signal measurement of a radio environment of a mobile device and a respective location estimate. The method also includes determining whether the location of the mobile device is part of a routine or deviates from a routine and, in case the location of the mobile device is part of a routine, at least partially performing the collecting of radio fingerprints with a reduced collecting scope compared to a collecting scope used in case the location of the mobile device deviates from a routine. The collecting of radio fingerprints, when the location of the mobile device is part of a routine, is configured such that, after collecting radio fingerprints for multiple occurrences of the respective routine, a coverage of the respective routine by the collected radio fingerprints is increased.

A method for generating an indoor environment model of a building comprises forming a transmitter location model for defining positions of transmitters in said building using gathered information for establishing transmitter locations (302), receiving signal strength indicative measurements being determined for a number of transmitters using at least one electronic communications device (304), wherein the signal strength indicative measurements are based on a signal which has varying signal propagation characteristics in the indoor environment, and wherein said signal strength indicative measurements are acquired from a number of known locations in the building, identifying discrepancies of signal transmittance in said indoor environment based on said signal strength indicative measurements in relation to said transmitter location model (306), determining locations of signal hindering elements causing said discrepancies (308), and generating said indoor environment model including transmitter locations and said signal hindering elements (310).

A method for determining the position of a mobile or asset in an indoor location in a radio frequency system, the method comprising: a) generating a Wi-Fi multi-band fingerprint database using at least one multi-band Wi-Fi access point configured to simultaneously transmit multiple frequency band wireless signals; b) selecting a most probable frequency band having the highest probability function for a target location of the mobile or asset given one or more measured signals; c) selecting one or more fingerprints from the Wi-Fi multi-band fingerprint database in dependence on the selected frequency band and selecting a measured signal that is needed to determine the location in dependence on the said most probable frequency band for each Wi-Fi access point; and d) comparing the selected measured signal and the selected one or more fingerprints to determine the location of the measured signal in dependence on a location estimation algorithm.

The present invention discloses, inter alia, a computerized system for building a multisensory location map, the system comprising an interface for receiving multiple multisensory data vectors acquired by multiple mobile devices at multiple locations and accelerometer readings obtained upon movement of at least one device carried by at least one user between the multiple locations; at least a portion of said movement being walking; at least a majority of the multiple locations are located within an area in which an accuracy of global positioning system (GPS) based navigation is below an allowable threshold; and a processor, interconnected with said interface, with accelerometers, a magnetometer and a map calculator, configured for: extracting, out of accelerometer readings, accelerometer information related to multiple walking phases of the walking; for at least two of said multiple walking phases, real-time correcting a currently measured Z vector, and a pitch angle and a roll angle thereof, thereby compensating for horizontal accelerations, thereby obtaining a Z vector pointing toward Earth's center; calculating, from said Z vector pointing toward earth's center, a surface parallel to Earth's face (perpendicular to said Z vector pointing toward earth's center); estimating, from said surface parallel to Earth's face and from a magnetic north measured by at least one built-in magnetometer in said at least one device, an offset selected from a group consisting of: an azimuth offset from magnetic north and a heading offset from geometric north; processing the accelerometer information related to said at least two of said multiple walking phases to determine a direction of propagation of the at least one user and correcting said direction of propagation based on said offset; and estimating, from said corrected direction of propagation, at least one location of said at least one user; and the map calculator calculating, in response to the multiple multisensory data vectors and said at least one estimated location, a location fingerprinting map that comprises multiple grid points; each of the multiple grid points comprising a multisensory grid point fingerprint and grid point location information derivable from said at least one estimated location.

In one embodiment, a technique is provided for wireless position determination wherein identification information and positional information about wireless beacons is downloaded to a local database of a wireless computing device from a central database. The local database is usable by a wireless positioning system of the wireless computing device to estimate a position of the wireless computing device. A receiver unit of the wireless computing device may receive signals from wireless beacons that include a least one new wireless beacon not included in the local database. The wireless positioning system estimates positional information of the at least one new wireless beacon based on the position of the wireless computing device. Identification information and positional information for the at least one new wireless beacon is added to the local database. Thereafter, a contribution may be uploaded to the central database for the at least one wireless beacon, to further build the central database.

According to the present invention, a radio map construction method uses a genetic algorithm and comprises the steps of: (a) generating a plurality of chromosomes, each including a set of pairs consisting of a fingerprint labeled with an address and a position selected within a region s of the address; (b) generating a temporary radio map by using the pairs of the chromosomes; (c) arranging collected fingerprint sequences by using the temporary radio map; and (d) evaluating the placement of the fingerprint sequences.

Results of measurements by a mobile device on radio signals transmitted by at least one transmitter are obtained. The results of measurements comprise characteristics of the radio signals at each of a plurality of locations of measurements at a particular site, and indications of the locations of measurement. The results of measurement and the indications of the locations are provided and used as a basis for a generation of a radio map for use in supporting a positioning of mobile devices at the site. In addition, a user input to the mobile device is detected, the user input defining a localization area at the site that is to be covered by the radio map. A representation of the defined localization area is provided in addition for use in connection with the radio map.

Disclosed are various embodiments that enable the identification of the location of a computing device based on radio data. A radio map can be identified for an area. The computing device can measure signal strengths to reference points. The signal strengths can be compared to the radio map. The computing device can determine its location based on the comparison of the signal strengths to the radio map.

An indoor target positioning method based on an improved convolutional neural network (CNN) model includes acquiring and preprocessing target camera serial interface (CSI) data of a to-be-positioned target and matching the preprocessed target CSI data with fingerprints in a positioning fingerprint database to obtain coordinate information of the to-be-positioned target. The generation method of the positioning fingerprint database includes: collecting indoor WiFi signals by a software defined radio (SDR) platform to obtain indoor CSI data corresponding to the WiFi signals, and preprocessing the indoor CSI data; partitioning the preprocessed indoor CSI data into a plurality of data subsets through a clustering algorithm; training an improved CNN model by the data subsets to obtain a trained improved CNN model; and generating the positioning fingerprint database by the trained improved CNN model and the preprocessed indoor CSI data.