U-Blox Ag

Matthias Mahlig

Dimitris Kalogiros

Ioannis Sarris

Peter Karlsson

Hariharasudhan Vigneswaran

Stelios Papaharalabos

Timon Merk

Farshid Rezaei

Calibrating an anchor point in a positioning system includes, in an example implementation, transmitting a localization signal between a mobile device and the anchor point, determining a first direction between the mobile device and the anchor point in a local coordinate system based on the transmitted localization signal, and determining a second direction between the mobile device and the anchor point in a global coordinate system based on the determined first direction and a stored anchor orientation of the anchor point, the anchor orientation defining the local coordinate system of the anchor point with respect to the global coordinate system. Calibrating the anchor point further includes acquiring a target position of the mobile device, the target position being associated with the transmitted localization signal, determining a third direction between the mobile device and the anchor point in the global coordinate system based on a known anchor position and the target position, and adjusting the stored anchor orientation based on the first direction and a difference between the second and the third direction.

Method for calibrating an anchor point and device for a positioning system

A method for detecting anomalies in a positioning system comprises receiving, for a plurality of locator devices (ANC, ANC, ANC, ANC), respective location indicators associated with at least one mobile device (TG, TG, TG), determining a position of the at least one mobile device (TG, TG, TG) based on the received location indicators, acquiring, for at least one of the location indicators received, a confidence indicator associated with the at least one of the location indicators, determining, for each acquired confidence indicator, whether a confidence criterion is met, and storing an anomaly indicator in an anomaly cache, if the confidence criterion is not met, wherein each anomaly indicator is associated with the locator device, for which the location indicator is received; and generating an anomaly alert message for at least one of the locator devices based on an evaluation of the anomaly indicators that are stored for the at least one of the locator devices.

Method for detecting anomalies in a positioning system and positioning engine for a positioning system

An example method of determining a position of a mobile device includes, for each of a plurality of anchor points, receiving respective relative position information between the respective anchor point and the mobile device such that the received relative position information for the plurality of anchor points forms a set of position information, each relative position information including at least one of: a direction between the respective anchor point and the mobile device, a distance between the respective anchor point and the mobile device, or a direction and a distance between the respective anchor point and the mobile device. The method includes determining an estimated position of the mobile device based on the set of position information; defining a set of loci, each locus of the set of loci being based on one or more of the relative position information from the set of position information; determining, for each locus of the set of loci, a distance value between the estimated position of the mobile device and the respective locus; determining, for each locus of the set of loci, a weight factor as a function of the determined distance values; and determining a refined position of the mobile device based on the set of position information and the determined weight factors. A positioning engine for determining a position of a mobile device is disclosed as well.

Method and positioning engine for determining a position of a mobile device

The present disclosure relates to a method for determining an angle of arrival, AoA, of received radio frequency, RF, measurement signals. The method comprises obtaining measurement data based on the received RF measurement signals from an antenna array, wherein the RF measurement signals are representative of multiple frequency channels. The method further comprises determining power spectra, comprising determining at least one power spectrum for each of the multiple frequency channels by using the measurement data. The method further comprises providing a machine learning algorithm, which is pre-trained to determine an AoA based on power spectra of multiple frequency channels. The method further comprises determining the AoA of the received RF measurement signals by using the machine learning algorithm and the determined power spectra.

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Thalwil, Switzerland

Matthias Mahlig