A vehicle positioning method via data fusion and a system using the same are disclosed. The method is performed in a processor electrically connected to a self-driving-vehicle controller and multiple electronic systems. The method is to perform a delay correction according to a first real-time coordinate, a second real-time coordinate, real-time lane recognition data, multiple vehicle dynamic parameters, and multiple vehicle information received from the multiple electronic systems with their weigh values, to generate a fusion positioning coordinate, and to determine confidence indexes. Then, the method is to output the first real-time coordinate, the second real-time coordinate, and the real-time lane recognition data that are processed by the delay correction, the fusion positioning coordinate, and the confidence indexes to the self-driving-vehicle controller for a self-driving operation.

A positioning system that combines the use of real-time location system and a robotic total station into a single, transparent hybrid positioning system to locate one or multiple targets by one or multiple users.

A position identifying apparatus includes a position detecting unit; an information acquiring unit; a feature extracting unit; an index value calculating unit; a feature selecting unit; a correlating unit; a weight setting unit; and a correcting unit.

The position detecting unit performs a map matching to detect a vehicle position on a map. The information acquiring unit acquires road information from the map. The feature extracting unit extracts features of ground object. The index value calculating unit calculates an index value representing a likelihood of a stationary object. The feature selecting unit selects feature candidates among the features having the index values larger than or equal to a predetermined likelihood of the stationary object. The correlating unit correlates the feature candidates with the road information. The weight setting unit sets weights of the feature candidates. The correcting unit corrects the position of the vehicle using the weights.

Disclosed are techniques for processing satellite signals for computing a geospatial position. A plurality of GNSS signals are received from a plurality of GNSS satellites. An image is captured using an imaging device at least partially oriented toward the plurality of GNSS satellites. The image is segmented into a plurality of regions based on RF characteristics of objects in the image. An orientation of the image is determined. The plurality of GNSS satellites are projected onto the image based on the orientation of the image such that a corresponding region is identified for each of the plurality of GNSS satellites. Each of the plurality of GNSS signals is processed in accordance with the corresponding region.

A computerized system operable to provide multiple video streams of an event. In an ideal embodiment, the system provides live and dynamic streaming of an event such as a sporting event, concert, march, rally, and the like, to allow viewers to watch video of the event from nearly any angle and vantage point.

A vehicle, for example, an autonomous vehicle receives signals from a global navigation satellite system (GNSS) and determines accurate location of the vehicle using the GNSS signal. The vehicle performs localization to determine the location of the vehicle as it drives. The autonomous vehicle uses sensor data and a high definition map to determine an accurate location of the autonomous vehicle. The autonomous vehicle uses accurate location of the vehicle to determine RTK corrections that is used for improving GNSS location estimates at a future location. The RTK corrections may be transmitted to other vehicles.

A system includes a processor configured to request capture of image data of an environment surrounding the user, responsive to a margin of error of a detected location of a user being above a predefined threshold. The processor is also configured to process the image data to determine an actual user location relative to a plurality of objects, having known positions, identifiable in the image data and replace the detected location with the determined actual user location.

Systems are configured for performing GPS-based and sensor-based relocalization. During the relocalization, the systems are configured to obtain radio-based positioning data indicating an estimated position of the system within a mapped environment. The systems are also configured to identify, based on the estimated position, a subset of keyframes of a map of the mapped environment, wherein the map of the mapped environment includes a plurality of keyframes captured from a plurality of locations within the mapped environment, and the plurality of keyframes are associated with anchor points identified within the mapped environment. The systems are further configured to perform relocalization within the mapped environment based on the subset of keyframes.

An optical positioning-navigation-timing (PNT) system includes a managed optical communications array (MOCA) transceiver. The MOCA transceiver includes an array of optical transceivers for transmitting and receiving optical signals, each optical transceiver including a laser and a beam steering element, and a controller for controlling the operation of the array of optical transceivers. Each optical transceiver is adjustable for optical parameters of the optical signals so transmitted and received, the optical parameters including at least one of phase, angle, wavelength, time delay, amplitude, pulse delay, polarization, timing offset, phase, and divergence angle. Further, the controller is configured for controlling the optical parameters to include PNT data in a portion of the optical signal transmitted from the MOCA transceiver.

An embodiment relates to a method for performing operations related to a vulnerable road user (VRU) by a road side unit (RSU) in a wireless communication system, the operations comprising: receiving, by the RSU, personal safety messages (PSMs) of a VRU; determining, by the RSU, location information of the VRU on the basis of first location information of the VRU obtained through image information and second location information of the VRU obtained through the PSMs; and transmitting, by the RSU, the location information of the VRU to the VRU.