The description relates to mobile device location. One example can identify global navigation satellite system (GNSS) satellites expected to be in line-of-sight of a mobile device. This example can detect differences between received GNSS data signals and expected GNSS data signals from the expected GNSS satellites. The example can also determine a direction from the mobile device of an obstruction that is causing at least some of the detected differences.

A localization server improves position estimates of global navigation satellite systems (GNSS) using probabilistic shadow matching and pseudorange matching is disclosed herein. The localization server may utilize one or more of the following information: the locations of the satellites, the GNSS receiver's location estimate and associated estimated uncertainty, the reported pseudoranges of the satellites, the GNSS estimated clock bias, the SNRs of the satellites, and 3D environment information regarding the location of the receiver. The localization server utilizes a Bayesian framework to calculate an improved location estimate using the GNSS location fixes, pseudorange information, and satellite SNRs thereby improving localization and tracking for a user device.

Examples for determining velocity using a reflected positioning signal are presented herein. An example may involve a receiver receiving signals from satellites and identifying a particular signal that reflected off a reflecting plane prior to reaching the receiver. The receiver may then determine a reflected satellite position for a satellite that transmitted the particular signal. The reflected satellite position may be determined by reflecting a position of the satellite about the reflecting plane. The receiver may then determine a direction vector to the reflected satellite position for the satellite and determine its velocity using the determined direction vector.

Sets of digital samples associated with received wireless signals are received, each of the sets of digital samples corresponding to a particular RF path. The sets of digital samples are provided to a plurality of pipelines, each of the plurality of pipelines including a plurality of stages, each of the plurality of stages including one or more digital logic circuits. Sets of interconnect data are generated by the plurality of pipelines based on the sets of digital samples, the sets of interconnect data including at least one accumulating value. The sets of interconnect data are passed between adjacent pipelines of the plurality of pipelines along a direction. A result is generated by a last pipeline of the plurality of pipelines based on the at least one accumulating value.

Methods and systems include localization of a vehicle localize precisely and in near real-time. As described, localization of a vehicle using a Global Navigation Satellite System (GNSS) can comprise receiving a signal from each of a plurality of satellites of a GNSS constellation and receiving input from one or more sensors of the vehicle. The input from the sensors can indicate current physical surroundings of the vehicle. A model of the current physical surrounding of the vehicle can be generated based on the input from the one or more sensors of the vehicle. One or more multipath signals received from the plurality of satellites can be mitigated based on the model and the vehicle can be localized using the received signals from the plurality of satellites of the GNSS constellation and based on the mitigation of the one or more multipath signals.

Global navigation satellite systems and methods use L5 GNSS signals to acquire secondary code phases of those signals without using L1 GNSS signals to aid in the acquisition of secondary code phases. Various embodiments are described to perform this acquisition.

This positional error prediction device (1) is provided with: a satellite position acquisition unit (154) which acquires a receivable position of a satellite on a target date at a target time and a target point at which a positional error prediction is performed; a relative relationship value acquisition unit (151) which acquires a value of the relative relationship between the position of the satellite and an observation start position of the satellite at the target point; and an error prediction unit (155) which predicts, on the basis of the relative relationship value and a positional error prediction model generated in advance, a positional error on the target date at the target time and the target point.

Methods and systems include localization of a vehicle localize precisely and in near real-time. As described, localization of a vehicle using a Global Navigation Satellite System (GNSS) can comprise receiving a signal from each of a plurality of satellites of a GNSS constellation and receiving input from one or more sensors of the vehicle. The input from the sensors can indicate current physical surroundings of the vehicle. A model of the current physical surrounding of the vehicle can be generated based on the input from the one or more sensors of the vehicle. One or more multipath signals received from the plurality of satellites can be mitigated based on the model and the vehicle can be localized using the received signals from the plurality of satellites of the GNSS constellation and based on the mitigation of the one or more multipath signals.

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.

To accurately determine walking routes with roadways interposed therebetween. An environmental value calculation unit (18) calculates, based on a plurality of satellite signals from a plurality of satellites received by a positioning apparatus held by a pedestrian of object, an environmental value indicating whether a reception environment of a satellite signal of the plurality of satellite signals is good or bad for a left half side and a right half side with reference to a traveling direction of the pedestrian, and a route determination unit (20) compares an environmental value of the left half side calculated by the environmental value calculation unit (18) with an environmental value of the right half side calculated by the environmental value calculation unit (18) to determine a walking route of the pedestrian.