The disclosed subject matter relates to an Intelligent Transportation System station (ITS-S) for being carried by a Vulnerable Road User (VRU), comprising: a motion sensor for determining VRU motion data indicative of a VRU position, a VRU speed, and a VRU heading; a transmitter for transmitting a VRU message including the determined VRU motion data; a receiver for receiving, concerning a vehicle, vehicle motion data indicative of a vehicle position, a vehicle speed, and a vehicle heading; and a controller for controlling the transmitter; wherein the controller is configured to compare the determined VRU motion data with the received vehicle motion data and, when the result of the comparison meets a predetermined criterion, to suppress the transmitting of said VRU message.

A satellite positioning receiver includes a local oscillator, a front-end circuit with having an analog mixer, a number of signal processing channel circuits, and a processing circuit. The satellite positioning receiver performs a method that includes (i) acquiring a first satellite using a first frequency search space that spans both uncertainties due to the first satellite's orbit and uncertainties due to the clock bias or a time rate of change of the bias; and (ii) using the bias or the time derivative of the bias determined during the acquisition of the first satellite, acquiring a second satellite using a second frequency search space that spans substantially only uncertainties due to the second satellite's orbit.

Techniques are provided for utilizing a mobile device to estimate ionospheric delays in GNSS transmissions. An example method of determining a position of a mobile device includes obtaining a pseudorange measurements and carrier-phase measurements for a satellite at a first frequency band and a second frequency band, determining a bias estimate for the satellite based on a plurality of pseudorange measurements and carrier-phase measurements, determining a delta carrier-phase measurement for the satellite based on the carrier-phase measurements at the first frequency band and the second frequency band, and determining the position of the mobile device based at least in part on the delta carrier-phase measurement, and the pseudorange measurements, the carrier-phase measurements, or both.

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 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.

As a computing device travels on a trip from a starting location to a destination location, geographic coordinates are captured and stored. The geographic coordinates are tested against an obscuring condition to determine a portion of the geographic coordinates that satisfy the obscuring condition. Based on the determined portion of geographic coordinates satisfying the obscuring condition, altering the geographic coordinates in the determined portion of the geographic coordinates to reduce their precision or accuracy. The computing device transmits the altered geographic coordinates and the geographic coordinates that did not satisfy the obscuring condition.

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 golf rangefinder system comprises a GPS golf rangefinder device and an accessory. The golf rangefinder device comprises a housing defining a forward housing portion with a display screen viewable therein, and a rearward housing portion with a convexity projecting therefrom. A magnet centrally positioned at a distal most portion of the convexity. The accessory includes a clip with a hook-shaped member and a receptacle portion for mating with the convexity of the housing of the golf rangefinder device. A second magnet is positioned in a recess in the receptacle portion. The receptacle portion configured as a concavity and conforming to the convexity of the rangefinder device whereby when the accessory and rangefinder device are in proximity with each other they are magnetically coupled with the convexity positioned in the concavity. The accessory and rangefinder slidably rotatable and movable with respect to one another while still maintaining the magnetic coupling.