Abstract: A method of modeling mutable environmental structures includes receiving an estimated location of a Global Navigation Satellite Systems (GNSS) receiver in an environment and a plurality of GNSS-related features corresponding to a GNSS signal received at the GNSS receiver. The method also includes determining a plurality of candidate positions about the estimated location for the GNSS receiver. Each candidate position corresponds to a possible actual location of the GNSS receiver in the environment. For each candidate position, the method further includes generating, as an output from a GNSS localization model configured to receive the plurality of GNSS-related features as input, a respective probability that the respective candidate position includes the actual location of the GNSS receiver. The method also includes selecting from the plurality of candidate positions, the respective candidate position having a greatest probability as the actual location of the GNSS receiver.

Abstract: 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.

Abstract: 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.

Abstract: A method of modeling mutable environmental structures includes receiving an estimated location of a Global Navigation Satellite Systems (GNSS) receiver in an environment and a plurality of GNSS-related features corresponding to a GNSS signal received at the GNSS receiver. The method also includes determining a plurality of candidate positions about the estimated location for the GNSS receiver. Each candidate position corresponds to a possible actual location of the GNSS receiver in the environment. For each candidate position, the method further includes generating, as an output from a GNSS localization model configured to receive the plurality of GNSS-related features as input, a respective probability that the respective candidate position includes the actual location of the GNSS receiver. The method also includes selecting from the plurality of candidate positions, the respective candidate position having a greatest probability as the actual location of the GNSS receiver.

Abstract: Systems and methods for determining semantic travel modes are provided. In one embodiment, a method can include obtaining, by one or more computing devices, a plurality of location reports from a user device. Each of the plurality of location reports can include at least a set of data indicative of an associated location and time. The method can further include obtaining, by the one or more computing devices, one or more geographic signals that comprise a set of data associated with one or more geographic locations. The method can include determining, by the one or more computing devices, a semantic travel mode associated with the user device based at least in part on the plurality of location reports and the one or more geographic signals.

Abstract: Systems and methods for determining semantic travel modes are provided. In one embodiment, a method can include obtaining a plurality of location reports from a user device. Each of the plurality of location reports can include at least a set of data indicative of an associated location and time. The method can further include determining a travel period associated with the user device based on the plurality of location reports. The method can include obtaining one or more personalization signals that include a set of data associated with a semantic travel mode. The method can include determining that the user device is associated with the semantic travel mode during the travel period based at least in part on the plurality of location reports and the one or more personalization signals.

Abstract: Systems and methods are provided for determining a user context based on one or more wireless signals. In particular, location data can be determined by a user device. The user device can then detect beacon data broadcast by a first set of beacon devices, and subsequent to detecting the first beacon data, second beacon data broadcast by a second set of beacon devices. The location data can be compared with the first beacon data and the second beacon data to determine a user context. In particular, a context can be determined based at least in part on whether the location data is indicative of a changing location of a user, and whether the second beacon data corresponds to a change in beacon data from the first beacon data.