A chip-scale gyrometric apparatus is disclosed. In embodiments, the chip-scale gyrometric apparatus includes a dielectric substrate and an antenna element attached thereto for receiving an inbound signal having an initial phase. The apparatus includes a splitter for splitting the inbound signal into two equivalent signals, and two coils connected to the splitter. The first coil carries one of the split signals in a clockwise (CW) path relative to a rotational axis, while the second coil carries the other split signal in a counterclockwise (CCW) path relative to the same axis. An integrated circuit (IC) on the substrate and connected to the first and second coils measures a phase shift between the first and second signals (e.g., deviation from the initial phase) based on their respective CW and CCW paths and determines, based on the measured phase shift, a degree of rotation relative to the common rotational axis.

Provided is a navigation board, a multi-source data fusion method for a navigation board and a transporter. The navigation board includes a printed circuit board, a global navigation satellite system module, an inertial sensor, a processor, and a data interface; the processor is configured to execute a large misalignment angle initialization algorithm, an inertial strapdown solution algorithm, and a multi-source data fusion solution; and a size of the navigation board is smaller than or equal to a size of a standard GNSS board, and the navigation board at least includes the same data interface as a data interface of the standard GNSS board.

A method for navigating a carrier using a Kalman filter estimating a navigation state of a carrier, comprising: obtaining, from a signal transmitted by the satellite and subsequently received by the carrier, a delta range measured between the carrier and a satellite and another measured kinematic datum which is associated with the satellite, generating, from position data for the carrier and the satellite in the navigation state, an estimated delta range between the carrier and the satellite, calculating, using the delta ranges, a delta range innovation associated with the satellite, carrying out a test on the delta range innovation, the test result indicating whether or not the signal was a multi-path signal, using, by means of the filter, the kinematic datum as an observation to update the navigation state provided that the test result indicates that the signal was not a multi-path signal.

A vehicle computing system validates location data received from a Global Navigation Satellite System receiver with other sensor data. In one embodiment, the system calculates velocities with the location data and the other sensor data. The system generates a probabilistic model for velocity with a velocity calculated with location data and variance associated with the location data. The system determines a confidence score by applying the probabilistic model to one or more of the velocities calculated with other sensor data. In another embodiment, the system implements a machine learning model that considers features extracted from the sensor data. The system generates a feature vector for the location data and determines a confidence score for the location data by applying the machine learning model to the feature vector. Based on the confidence score, the system can validate the location data. The validated location data is useful for navigation and map updates.

A method includes: receiving one or more positioning signals; determining that a UE is line-of-sight to fewer than a threshold number of positioning signal sources; determining a first position estimate hypothesis for the UE using a first position estimating process and one or more first measurements of the positioning signal(s); determining a second position estimate hypothesis for the UE using a second position estimating process and one or more second measurements of the positioning signal(s), wherein the second position estimating process uses a second parameter value of a parameter and the parameter is absent from the first position estimating process or has a first parameter value that is different from the second parameter value; and reporting a reported position estimate based on the first position estimate hypothesis or the second position estimate hypothesis in response to the UE being line-of-sight to fewer than the threshold number of positioning signal sources.

The techniques discussed herein may comprise an autonomous vehicle guidance system that generates a path for controlling an autonomous vehicle based at least in part on a static object map and/or one or more dynamic object maps. The guidance system may identify a path based at least in part on determining set of nodes and a cost map associated with the static and/or dynamic object, among other costs, pruning the set of nodes, and creating further nodes from the remaining nodes until a computational or other limit is reached. The path output by the techniques may be associated with a cheapest node of the sets of nodes that were generated.

A method for processing GPS position signals in a vehicle is proposed, wherein the GPS position signals of the vehicle are received successively at a predefined time interval and are processed in order to control the vehicle, and wherein at least one intermediate position value of the vehicle is determined within the time period formed by the time interval between two successive GPS position signals. Furthermore, a control device is proposed for carrying out the method.

A method for generating a physical model of a path from GPS data. The method involves receiving GPS data defining a path from a GPS-enabled device and receiving a digital terrain model for an area that includes the path. An area of interest along the path is then identified and the GPS data associated with the area of interest is smoothed. The digital terrain model is sampled along the path and an elevation of the path is smoothed using a weighted average of the digital terrain model and the GPS data to create modified path data that is scaled to produce a first ribbon that is printed.

A systems and methods for ridesharing are provided. The systems and method can include splitting a plurality of GPS locations for a given vehicle into segments, determining a most probable location for each GPS location, and reconstructing the route, for a fleet of ridesharing vehicles.

Systems and methods for synchronization are provided. In some aspects, a method for synchronizing an image sensor is provided. The method includes receiving image data captured using an image sensor that is moving along a pathway, and assembling an image sensor trajectory using the image data. The method also includes receiving position data acquired along the pathway using a position sensor, wherein timestamps for the image data and position data are asynchronous, and assembling a position sensor trajectory using the position data. The method further includes generating a spatial transformation that aligns the image sensor trajectory and position sensor trajectory, and synchronizing the image sensor based on the spatial transformation.