A method, performed by at least one apparatus, is provided that includes obtaining first radio map data. The first radio map data indicates geographic positions with respect to a first coordinate system. The method also obtains second radio map data. The second radio map data indicates geographic positions with respect to a second coordinate system. The method further includes identifying a transformation between the first coordinate system and the second coordinate system and applying the identified transformation at least to a part of the first radio map data and/or the second radio map data. A corresponding apparatus and computer readable storage medium are also provided.

To perform positioning by a computing device, a position request transmitted by a terminal is received. The positioning request includes target access point information obtained by the terminal. Then a plurality of first geographic grids related to a location of the terminal is determined based on the target access point information. A positioning sequence of the plurality of first geographic grids is determined according to access point information corresponding to the plurality of first geographic grids and the target access point information. The positioning sequence indicates distances between the plurality of first geographic grids and the terminal. The location of the terminal is then determined based on the positioning sequence of the plurality of first geographic grids and location information of the plurality of first geographic grids.

Device-free localization for smart indoor environments within an indoor area covered by wireless networks is detected using active off-the-shelf-devices would be beneficial in a wide range of applications. By exploiting existing wireless communication signals and machine learning techniques in order to automatically detect entrance into the area, and track the location of a moving subject within the sensing area a low cost robust long-term tracking system can be established. A machine learning component is established to minimize the need for user annotation and overcome temporal instabilities via a semi-supervised framework. After establishing a robust base learner mapping wireless signals to different physical locations from a small amount of labeled data; during its lifetime, the learner automatically re-trains when the uncertainty level rises significantly. Additionally, an automatic change-point detection process is employed setting a query for updating the outdated model and the decision boundaries.

Systems and methods for WiFi mapping an industrial facility are disclosed. The system comprises a self-driving vehicle having a WiFi transceiver. The self-driving vehicle communicates with a fleet-management using the WiFi transceiver, via a WiFi access point. The self-driving vehicle receives a mission from the fleet-management system, and moves to a destination location based on the mission, using autonomous navigation. While executing the mission, the self-driving vehicle simultaneously measures the received signal strength indication of the WiFi access point and other WiFi access points in the facility, and stores the received signal strength indication in association with the location at which the received signal strength indication was measured.

A method, electronic device and apparatus are disclosed. The method comprises obtaining a plurality of fingerprints. Each fingerprint is determined by a respective radio node. One or more respective signals are sent by one or more respective radio nodes surrounding the respective radio node. Each fingerprint comprises a respective piece of position information that is indicative of the respective location of the radio node that determined the fingerprint. Each fingerprint further comprises at least one respective piece of identifier information associated with and uniquely identifying the respective one or more radio nodes surrounding the respective radio node. The method also includes generating a radio map based at least on the fingerprints; determining a further radio measurement for a current location of the electronic device; and determining the position of the electronic device based at least on the determined further radio measurement and the generated radio map.

A method of operating an indoor location services system includes providing a calibration beacon signal from a calibration device at a number of calibration locations, measuring a received signal strength of the calibration beacon signal at each one of a number of receivers for each one of the number of calibration locations, measuring a received signal strength of a beacon signal provided by a locatable device at each one of the receivers, and estimating a location of the locatable device based on the received signal strength of the beacon signal at each one of the receivers, the received signal strength of the calibration beacon signal at each one of the receivers for each one of the calibration locations, and a location of each one of the receivers.

Collocated access point (AP) harvest data is combined with accurate location-tagged harvest data to improve access point location estimates and to estimate the location of access points that could not be previously estimated.

Systems and methods for WiFi mapping an industrial facility are disclosed. The system comprises a self-driving vehicle having a WiFi transceiver. The self-driving vehicle communicates with a fleet-management using the WiFi transceiver, via a WiFi access point. The self-driving vehicle receives a mission from the fleet-management system, and moves to a destination location based on the mission, using autonomous navigation. While executing the mission, the self-driving vehicle simultaneously measures the received signal strength indication of the WiFi access point and other WiFi access points in the facility, and stores the received signal strength indication in association with the location at which the received signal strength indication was measured.

The present invention is a system and method for detecting and locating the transmission of radio frequency signals from within a defined geographical area. The system uses statistical confidence limits to detect outliers caused by transmissions in the defined geographical area. The source of the transmission can then be located with triangulation.

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.