A signal generation system for signal simulation includes at least one data input, a pulse description word generator, a multi-frequency signal generator, and at least one radio frequency output. The multi-frequency signal generator is configured to simulate a multi-frequency global navigation satellite system signal. The pulse description word generator and the multi-frequency signal generator are assigned to the data input in order to process data received via the data input. The pulse description word generator and the multi-frequency signal generator are configured to generate an output signal based on at least one instruction for a certain generator behavior of the pulse description word generator and/or the multi-frequency signal generator. The at least one instruction is encompassed in the data received. Further, a method of signal generation is described.

A device implementing a system for estimating device location includes at least one processor configured to receive an estimated position based on a positioning system comprising a Global Navigation Satellite System (GNSS) satellite, and receive a set of parameters associated with the estimated position. The processor is further configured to apply the set of parameters and the estimated position to a machine learning model, the machine learning model having been trained based at least on a position of a receiving device relative to the GNSS satellite. The processor is further configured to provide the estimated position and an output of the machine learning model to a Kalman filter, and provide an estimated device location based on an output of the Kalman filter.

Method, apparatuses, and computer program products for automatically tracking a heading of an object. An example method comprising receiving, one or more internal measurement values which pertain to an object; determining an internal heading uncertainty value for each internal measurement value of the one or more internal measurement values; generating, using a probabilistic heading model, an estimated heading data object for the object based at least in part on the one or more internal measurement values; and providing the estimated heading data object to one or more associated user devices.

A system is disclosed for determining a physical metric such as position. The system comprises a local signal generator (8) configured to provide a local signal and a receiver (4) configured to receive a signal having properties corresponding to those in a signal transmitted by a trusted remote source. An inertial measurement unit (12) is configured to provide a measured or assumed movement of the receiver. A correlator (6) is configured to provide a correlation signal by correlating the local signal with the received signal. A motion compensation unit (14) is configured to provide motion compensation of at least one of the local signal, the received signal, and the correlation signal based on the measured or assumed movement. A signal analysis unit (16) is configured to determine whether the received signal includes a component received in a direction that is different to a line-of-sight direction between the receiver and the trusted remote source, wherein the determination is based on the correlation signal. Finally, a metric determination unit or positioning unit (20) is configured to determine a physical metric associated with the receiver, such as its position, based on the determination made by the signal analysis unit (16).

A method, apparatus and computer program product are provided for detecting multipath signals from a navigation satellite. In the context of a method, the method includes obtaining a measurement of a parameter based on signals transmitted by the navigation satellite and received by a navigation device and determining an estimated position of the navigation device upon receiving the signals. Based on navigation data regarding a position of the navigation satellite and correction data regarding a correction to the position of the navigation satellite, the method also includes determining a virtual observation for the parameter. The virtual observation is determined for the navigation device being located at the estimated position. The method further includes determining whether the signals transmitted by the navigation satellite and received by the navigation device include multipath signals based upon the measurement of the parameter and the virtual observation for the parameter.

A method of processing signal paths includes receiving an estimated location for a GNSS receiver in an environment. The method also includes generating a plurality of candidate positions about the estimated location where each candidate position corresponds to a possible actual location of the GNSS receiver. The method further includes, for each available satellite at each candidate position, modeling a plurality of candidate signal paths by ray-launching a raster map of geographical data. Here, the plurality of candidate signal paths includes one or more reflected signal paths. At each candidate position, the method also includes comparing, the plurality of candidate signal paths modeled for each available satellite at the respective candidate position to measured GNSS signal data from the GNSS receiver and generating a likelihood that the respective candidate position includes the actual location of the GNSS receiver based on the comparison.

Methods and systems disclosed herein may include receiving signals from a transmitter in a receiver; determine a bias of the transmitter and receiver; generating expected observations, based on the bias, corresponding to the received signals; and calculate a building height based on a power level of the received signals and a power level of the expected observations.

Method, apparatuses, and computer program products for automatically tracking a heading of an object. An example method comprising receiving, one or more internal measurement values which pertain to an object; determining an internal heading uncertainty value for each internal measurement value of the one or more internal measurement values; generating, using a probabilistic heading model, an estimated heading data object for the object based at least in part on the one or more internal measurement values; and providing the estimated heading data object to one or more associated user devices.

In some aspects, a mobile device is configured to obtain a set of satellite signal measurements through measuring, for each satellite in a first plurality of satellites, a first signal from the satellite in a first frequency band and a second signal from the satellite in a second frequency band. The first plurality of satellites can include at least a first satellite, a second satellite, and a third satellite. The mobile device can determine that at least one measurement in the set of satellite signal measurements is impaired, based on a difference between a measurement of the first signal from a particular satellite (e.g., the first satellite, the second satellite, or the third satellite) and a measurement of the second signal from the particular satellite. A position of the mobile device can then be determined based on non-impaired measurements in the set of satellite signal measurements.

A device implementing a system for estimating device location includes at least one processor configured to receive an estimated position based on a positioning system comprising a Global Navigation Satellite System (GNSS) satellite, and receive a set of parameters associated with the estimated position. The processor is further configured to apply the set of parameters and the estimated position to a machine learning model, the machine learning model having been trained based at least on a position of a receiving device relative to the GNSS satellite. The processor is further configured to provide the estimated position and an output of the machine learning model to a Kalman filter, and provide an estimated device location based on an output of the Kalman filter.