A device implementing a system for estimating device position includes at least one processor configured to receive a first sensor measurement of a device at a first time, the first sensor measurement having a first variance in measurement error, and to receive a second sensor measurement of the device at a second time, the second sensor measurement having a second variance in measurement error. The at least one processor is further configured to determine a speed of the device based on at least one of the first or second sensor measurements, and adjust the second variance in measurement error based on the determined speed. The at least one processor is further configured to estimate a device position based at least in part on the first variance in measurement error and the adjusted second variance in measurement error.

A method of determining a posterior error probability distribution for a parameter measured by a Global Navigation Satellite System (GNSS) receiver. The method comprises receiving a value for each of one or more GNSS measurement quality indicators associated with the GNSS measurement of the parameter. The or each received measurement quality indicator value is provided as an input into a multivariate probability distribution model to determine the posterior error probability distribution for the GNSS measurement, wherein the variates of the multivariate probability distribution model comprise error for said parameter, and the or each measurement quality indicator.

A method of determining a posterior error probability distribution for a parameter measured by a Global Navigation Satellite System (GNSS) receiver. The method comprises receiving a value for each of one or more GNSS measurement quality indicators associated with the GNSS measurement of the parameter. The or each received measurement quality indicator value is provided as an input into a multivariate probability distribution model to determine the posterior error probability distribution for the GNSS measurement, wherein the variates of the multivariate probability distribution model comprise error for said parameter, and the or each measurement quality indicator.

A train position detection apparatus is configured to detect a position of a train by receiving positioning radio waves from satellites through a reception antenna. The train position detection apparatus includes: a memory that stores therein in advance a railway design standard of a railway track on which the train travels; and one or more hardware processors that detect a position of the train by self-contained navigation based on an input signal from a self-contained navigation sensor. When a result of the train position detection based on the positioning radio waves does not satisfy the railway design standard, the one or more hardware processors correct the result of the train position detection based on the positioning radio waves with a result of the position detection by self-contained navigation.

Techniques are provided for GNSS carrier phase multipath mitigation using a blanked correlator in conjunction with a full correlator. A tracking loop may track a carrier of the GNSS signal utilizing the full correlator. A chip-edge accumulation (CEA) unit of the tracking loop may accumulate chip edges of a ranging code to generate CEA output. A blanked correlator may receive the CEA output to generate blanked correlator values. A running-sum filter may utilize the blanked correlator values to generate a running-sum value. A phase estimate may utilize the running-sum value to generate phase estimator output. In an exemplary embodiment, the blanked correlator operates as a monitoring correlator and the phases estimator output is the estimated carrier phase multipath error. In an exemplary embodiment, the blanked correlator provides input to the tracking loop and discriminator output is subtracted from the phase estimator output to generate the estimated carrier phase multipath error.

Techniques are provided for GNSS carrier phase multipath mitigation using a blanked correlator in conjunction with a full correlator. A tracking loop may track a carrier of the GNSS signal utilizing the full correlator. A chip-edge accumulation (CEA) unit of the tracking loop may accumulate chip edges of a ranging code to generate CEA output. A blanked correlator may receive the CEA output to generate blanked correlator values. A running-sum filter may utilize the blanked correlator values to generate a running-sum value. A phase estimate may utilize the running-sum value to generate phase estimator output. In an exemplary embodiment, the blanked correlator operates as a monitoring correlator and the phases estimator output is the estimated carrier phase multipath error. In an exemplary embodiment, the blanked correlator provides input to the tracking loop and discriminator output is subtracted from the phase estimator output to generate the estimated carrier phase multipath error.

A wireless device includes a satellite receiver to receive data from multiple satellites. The wireless device also includes processing circuitry and memory. The memory stores one or more neural network models. The processing circuitry is operative to identify a neural network model that has been trained to adapt to a region in which the wireless device operates, classify satellite raw measurements from each satellite at a given time into a corresponding quality level using the neural network model, and identify satellites raw measurements with a quality level higher than a threshold. The location of the wireless device is calculated using the identified satellite raw measurements.

An approach is provided for increased accuracy for a positioning receiver in a multipath signal environment. The approach, for example, involves receiving real-time imagery data collected using one or more sensors. The real-time imagery data, for instance, depicts a geographic environment in which the positioning receiver is operating. The approach also involves processing the real-time imagery data to dynamically generate a mask angle. The approach further involves blocking one or more signals from one or more navigation satellites received at the positioning receiver using the mask angle. The approach further involves determining positioning data using the positioning receiver based on the blocking of the one or more signals.

An approach is provided for increased accuracy for a positioning receiver in a multipath signal environment. The approach, for example, involves receiving real-time imagery data collected using one or more sensors. The real-time imagery data, for instance, depicts a geographic environment in which the positioning receiver is operating. The approach also involves processing the real-time imagery data to dynamically generate a mask angle. The approach further involves blocking one or more signals from one or more navigation satellites received at the positioning receiver using the mask angle. The approach further involves determining positioning data using the positioning receiver based on the blocking of the one or more signals.

A method for the satellite-supported determination of a position of a vehicle includes identifying a plurality of satellites which may be usable for determining a position of a vehicle and receiving data which characterize movable reception obstacles in a vicinity of the vehicle. The method includes determining a reduced selection of satellites from the plurality of satellites, based on the received data, and determining the position of the vehicle using signals which have been transmitted from the reduced selection of satellites.