Abstract: Subjects of the present disclosure are methods for training deep learning models, methods for predicting a map matching parameter, methods for updating a digital road map, and a computer program making it possible to implement the methods and devices for updating a digital road map. The general principle is based on the use of machine learning. Accordingly, a statistical deep learning model is trained according to a “supervised” machine learning scheme. Thereafter, the pretrained statistical deep learning model is used to predict a map matching parameter on the basis of a measurement of geographic coordinates and of an identifier of the position sensor that has performed the measurement of geographic coordinates. Finally, the map matching parameter can be used to update a digital road map.

Abstract: Locating a vehicle to be located (VP), which has at least a GNSS receiver, via a location system including at least a computer by: receiving a message that includes at least a GNSS signal and that is transmitted by the vehicle to be located (VP), receiving a message that is transmitted by at least one located vehicle (VL), which has a GNSS receiver, the message including a location of the vehicle, the location being associated with a high confidence level, and a GNSS signal generated by the GNSS receiver of the vehicle, determining a location of the vehicle to be located, on the basis of the location of at least one located vehicle (VL), the GNSS signal from the located vehicle, and the GNSS signal from the vehicle to be located, and transmitting the determined location to the vehicle to be located (VP).

Abstract: A method for determining a speed limit on a road segment on which a vehicle is travelling, including steps of obtaining a first speed limit by querying a geospatial database on the basis of a geographical location of the vehicle, of determining a confidence index associated with the first speed limit, of determining a second speed limit by analyzing at least one image obtained from a sensor of the vehicle, of determining a confidence index associated with the second speed limit, of selecting the speed limit associated with the highest confidence index, and of configuring an item of equipment of the vehicle on the basis of the speed limit associated with the highest confidence index.

Abstract: Locating a vehicle to be located (VP), which has at least a GNSS receiver, via a location system including at least a computer by: receiving a message that includes at least a GNSS signal and that is transmitted by the vehicle to be located (VP), receiving a message that is transmitted by at least one located vehicle (VL), which has a GNSS receiver, the message including a location of the vehicle, the location being associated with a high confidence level, and a GNSS signal generated by the GNSS receiver of the vehicle, determining a location of the vehicle to be located, on the basis of the location of at least one located vehicle (VL), the GNSS signal from the located vehicle, and the GNSS signal from the vehicle to be located, and transmitting the determined location to the vehicle to be located (VP).

Abstract: Subjects of the present disclosure are methods for training deep learning models, methods for predicting a map matching parameter, methods for updating a digital road map, and a computer program making it possible to implement the methods and devices for updating a digital road map. The general principle is based on the use of machine learning. Accordingly, a statistical deep learning model is trained according to a “supervised” machine learning scheme. Thereafter, the pretrained statistical deep learning model is used to predict a map matching parameter on the basis of a measurement of geographic coordinates and of an identifier of the position sensor that has performed the measurement of geographic coordinates. Finally, the map matching parameter can be used to update a digital road map.

Abstract: A GNSS receiver and the associated method, for calculating an unbiased position and time measurement from a plurality of satellite positioning signals, the receiver comprising: a plurality of circuits configured to receive positioning signals from a plurality of satellites in GNSS constellations, a plurality of first and second signal processing channels configured for processing a first selection of said positioning signals and determining associated first pseudo ranges, a computer logic, wherein: the computer logic is configured to calculate the unbiased position and time measurement from pseudo ranges being determined from positioning signals originating from distinct satellites. A GNSS receiver further comprising a second computer logic configured to calculate a second unbiased position and time from the first position and time, and the second signal processing signals.

Abstract: A GNSS receiver comprising a circuit configured to receive a positioning signal comprising a carrier modulated by a subcarrier and a PRN code; a subcarrier and code tracking loop, comprising a first discrimination circuit, configured to calculate a first pseudo range from said received positioning signal and a first reference signal; a code tracking loop, comprising a second discrimination circuit, configured to calculate a second pseudo range from said received positioning signal and a second reference signal; and a calculation circuit configured to evaluate a difference between said first pseudo range and said second pseudo range, and to modify the output of the first discrimination circuit accordingly. The invention further addresses a method for calculating a pseudo-range in such a GNSS receiver.

Abstract: A receiver, and associated process, for tracking a GNSS positioning signal comprising a carrier modulated by a subcarrier and a spreading code, the receiver comprising: at least one tracking loop configured to calculate a first pseudo range from said GNSS positioning signal, a first discrimination circuit (521) configured to calculate an ambiguous discriminator value from the subcarrier and the spreading code of said GNSS positioning signal, a calculation circuit (522) configured to calculate a value representative of a tracking error of said tracking loop, a second discrimination circuit (530) configured to select one of said ambiguous discriminator value and said value calculated by the calculation circuit, and to generate a first non-ambiguous discriminator value, an amplitude of which is based on an amplitude of the selected value, and a sign of which is a sign of said value calculated by the calculation circuit.

Abstract: A receiver, and associated process, for tracking a GNSS positioning signal comprising a carrier modulated by a subcarrier and a spreading code, the receiver comprising: at least one tracking loop configured to calculate a first pseudo range from said GNSS positioning signal, a first discrimination circuit (521) configured to calculate an ambiguous discriminator value from the subcarrier and the spreading code of said GNSS positioning signal, a calculation circuit (522) configured to calculate a value representative of a tracking error of said tracking loop, a second discrimination circuit (530) configured to select one of said ambiguous discriminator value and said value calculated by the calculation circuit, and to generate a first non-ambiguous discriminator value, an amplitude of which is based on an amplitude of the selected value, and a sign of which is a sign of said value calculated by the calculation circuit.

Abstract: A GNSS receiver and the associated method, for calculating an unbiased position and time measurement from a plurality of satellite positioning signals, the receiver comprising: a plurality of circuits configured to receive positioning signals from a plurality of satellites in GNSS constellations, a plurality of first and second signal processing channels configured for processing a first selection of said positioning signals and determining associated first pseudo ranges, a computer logic, wherein: the computer logic is configured to calculate the unbiased position and time measurement from pseudo ranges being determined from positioning signals originating from distinct satellites. A GNSS receiver further comprising a second computer logic configured to calculate a second unbiased position and time from the first position and time, and the second signal processing signals.

Abstract: A GNSS receiver comprising a circuit configured to receive a positioning signal comprising a carrier modulated by a subcarrier and a PRN code; a subcarrier and code tracking loop, comprising a first discrimination circuit, configured to calculate a first pseudo range from said received positioning signal and a first reference signal; a code tracking loop, comprising a second discrimination circuit, configured to calculate a second pseudo range from said received positioning signal and a second reference signal; and a calculation circuit configured to evaluate a difference between said first pseudo range and said second pseudo range, and to modify the output of the first discrimination circuit accordingly. The invention further addresses a method for calculating a pseudo-range in such a GNSS receiver.

Abstract: A radionavigation signal tracking device comprises a first and a second tracking stage for radionavigation signals. The first tracking stage comprises a first carrier phase-locked loop. The latter produces a first error signal arising from a phase difference between the first carrier and its replica. The phase of the replica of the first carrier is adjusted with the first error signal. The second tracking stage comprises a second carrier phase-locked loop. The latter produces a second error signal arising from a difference between the first phase difference and a phase difference between the second carrier and the replica thereof. The phase of the replica of the second carrier is adjusted with the first and second error signals.

Abstract: A radionavigation signal tracking device comprises a first and a second tracking stage for radionavigation signals. The first tracking stage comprises a first carrier phase-locked loop. The latter produces a first error signal arising from a phase difference between the first carrier and its replica. The phase of the replica of the first carrier is adjusted with the first error signal. The second tracking stage comprises a second carrier phase-locked loop. The latter produces a second error signal arising from a difference between the first phase difference and a phase difference between the second carrier and the replica thereof. The phase of the replica of the second carrier is adjusted with the first and second error signals.