Methods, devices, and systems are disclosed for home based electric vehicle (EV) charging. According to one embodiment, a method is implemented on at least one computing device. The method includes determining a plurality of media items for simultaneous viewing on a user interface (UI) associated with a home-based EV charger. The method further includes transmitting the plurality of media items to the UI associated with the home-based EV charger.

Techniques are provided which may be implemented using various methods and/or apparatuses in a vehicle to determine location relative to a roadside unit (RSU) or other nearby point of reference. Vehicles within a pre-designated range or within broadcast distance or otherwise geographically proximate to a roadside unit, through the use of broadcast or other messages sent by the vehicles and/or the RSU may share carrier GNSS phase measurement data, wherein the shared GNSS carrier phase measurement data may be utilized to control and coordinate vehicle movements, velocity and/or position by the RSU and/or to determine location of each vehicle relative to the RSU and/or to other vehicles or determine the absolute location of each vehicle. An RSU may coordinate vehicle access to an intersection, manage vehicle speeds and coordinate or control vehicle actions such as slowing, stopping, and changing lanes or sending a vehicle to a particular location.

Systems, methods, devices, computer readable media, and other various embodiments are described for location management processes in wearable electronic devices. Performance of such devices is improved with reduced time to first fix of location operations in conjunction with low-power operations. In one embodiment, low-power circuitry manages high-speed circuitry and location circuitry to provide location assistance data from the high-speed circuitry to the low-power circuitry automatically on initiation of location fix operations as the high-speed circuitry and location circuitry are booted from low-power states. In some embodiments, the high-speed circuitry is returned to a low-power state prior to completion of a location fix and after capture of content associated with initiation of the location fix. In some embodiments, high-speed circuitry is booted after completion of a location fix to update location data associated with content.

Machine learning techniques are used to compute predicted range rate errors in a GNSS receiver. In one embodiment, training data is computed to provide true range rate error data for a set of received GNSS signals. A system extracts features from the set of received GNSS signals and uses the extracted features and the true range rate error data to train a model (e.g., a set of one or more neural networks) that can produce predicted range rate errors for use in correcting measurements. The trained set of one or more neural networks can be deployed in GNSS receivers and used in the GNSS receivers to correct Doppler measurements using the predicted range rate errors provided by the trained set of one or more neural networks.

A network measurement device includes a setting control unit that sets, for example, a single GNSS as a transmission source of a signal of a multi-band, a multi-band abnormality detection unit that detects a multi-band reception abnormality based on an existing GNSS antenna receiving a signal in the multi-band transmitted from the GNSS, which is the transmission source, and reception signal information obtained by reception processing in a state in which the network measurement device is connected to the apparatus of a moving destination, for example, a boundary clock, and the existing GNSS antenna is connected to an antenna input terminal, for example, and an alert notification control unit that notifies a user of an alert notification that a multi-band reception abnormality occurs when a multi-band reception abnormality is detected.

Disclosed is a method for adaptive identification of erroneous GPS observed value, including: acquiring positioning information of a vehicle from a GPS sensor, and extracting first observed value data; acquiring posture information and speed information of the vehicle to acquire dead reckoning trajectory data of the vehicle; eliminating the erroneous GPS observed values based on respective data on data status value, heading significant bit, the number of satellites used and horizontal dilution of precision in the first observed value data to obtain second observed value data; constructing pose graph data based on the second observed value data and acquiring processing result information; analyzing and optimizing the processing result information to eliminate the erroneous GPS observed values of which the cost function exceeds a preset cost function threshold to obtain third observed value data; and constructing a high-precision map based on the third observed value data and three-dimensional scene map data.

Embodiments are disclosed for localization of vehicles using beacons. In an embodiment, a method comprises: determining, using at least one processor of a vehicle, that the vehicle has lost external signals (or is receiving degraded external signals) that are used for estimating a position of the vehicle; determining, using the at least one processor, a set of mobile beacons that are available to assist in estimating the position of the vehicle; receiving, using a communication device of the vehicle, broadcast signals from the set of mobile beacons, the broadcast signals including localization data for the set of mobile beacons; selecting, using the at least one processor, a subset of localization data from the set of mobile beacons for assisting in the position estimation of the vehicle; and estimating, using the at least one processor, the position of the vehicle using the subset of localization data.

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.

Systems and methods for determining a location of a mobile computing device requesting emergency services are provided. A mobile computing device may receive an indication of a request for emergency services from a user of the mobile computing device. The mobile computing device may receive a first wireless signal from a first device. The wireless signal may include an indication of a first geographic position associated with the first device. The mobile computing device may determine a location associated with the mobile computing device based on the indication of the first geographic position associated with the first device, and may send the determined location to a provider of emergency services.

A system and method, optionally implemented in a hardware circuitry, to receive a global positioning system pulse per second, GPS PPS, signal generated by a GPS receiver in a vehicle having a plurality of sensors; monitor the GPS PPS signal for an indication of a presence and a frequency of the GPS PPS signal within a predetermined threshold; generate a generated PPS signal synchronized with the GPS PPS signal; generate, based on an input of the generated PPS signal, a plurality of trigger signals, each of the generated plurality of trigger signals being selectively programmatically adjustable in at least one of a frequency and a phase, the selectively adjustability of each of the generated plurality of trigger signals being independent of the other generated plurality of trigger signals; and transmit at least one of the generated plurality of trigger signals to one or more of the sensors.