An object identification device according to the present invention includes: an acquisition unit that acquires, from a sensor that measures a position of an object and a speed of the object, sensor information measured by the sensor, and acquires size information from a device that transmits size information indicating a size and a position of the object; a designator adding unit that adds, to each piece of the sensor information, a sensor position designator indicating which part of the object is likely to be detected; and an information integration unit that determines, based on the sensor position designator, whether the object corresponding to the size information and the object corresponding to the sensor information are the same.

A vehicle radar device includes a first antenna unit, a second antenna unit, at least one computing unit and at least one circuit board. The first antenna unit and the second antenna unit are communicatively connected to the at least one computing unit. The at least one circuit board includes a first board portion and a second board portion. The first antenna unit is a circuit board type and disposed on the first board portion. The second antenna unit is a circuit board type and disposed on the second board portion. The at least one computing unit disposed on at least one of the first board portion and the second board portion. When an angle between the first board portion and the second board portion is P12, and the following condition is satisfied: 80 degreesP12130 degrees.

Aspects of the present disclosure involve a method for determining a road vehicle velocity and slip angle. The current disclosure presents a technique for identifying a vehicle's velocity and slip angle, in the vehicle's coordinate frame. In one embodiment, two or more sensors are orthogonally located on the underside of the vehicle in order to obtain longitudinal and lateral velocity information for slip angle determination. In another embodiment, the two or more sensors can include an array of elements for beam steering and receiver beamforming. Spatial diversity is leveraged in identifying at least a slip angle and/or velocity of the vehicle. Doppler mapping is used as a means for slip angle determination and the clutter ridge of the Doppler map is embraced for identifying the slip angle.

Various aspects of the disclosure relate to millimeter wave ranging with six degrees of freedom. For example, a multi-gigabyte link (e.g., an IEEE 802.11ad link or an 802.11ay link) and RF/Antenna diversity modules can be used to conduct round trip time (RTT) distance measurements between an anchor point and a station. Relative location information (e.g., degrees of freedom) between the wireless devices can then be determined based on the distance measurements.

A self-driving semi-truck can include tractor comprising a drive system, a first set of sensors mounted to the tractor, a fifth wheel, and cargo trailer comprising a kingpin coupled to the fifth wheel. The cargo trailer can include a Mansfield bar having a second set of sensors mounted thereto, where the second set of sensors have a rearward field of view from the trailer. The semi-truck can include an autonomous control system that receives sensor data from the first set of sensors and the second set of sensors, and analyzes the live sensor view to autonomously operate the drive system along a current route.

A system for tracking wearable user devices is provided herein. The system may include a tracking environment, comprising: one or more scene light sources, wherein the location of the scene light sources is known within said tracking environment; one or more scene detectors operable to detect light within the tracking environment, wherein the location and orientation of said one or more scene detectors is known within said tracking environment; one or more scene reflectors operable to reflect light originating from said one or more scene light sources, wherein the location of said one or more scene reflectors is known within said tracking environment; and, one or more wearable user devices comprising a curved reflective surface with known geometry; and, a computer processor operable to analyse light readings detected by said one or more scene detectors, and to calculate a position of the one or more wearable user devices.

Sensors, including radar sensors, may be used to detect objects in an environment. In an example, a vehicle may include multiple radar sensors that sense objects around the vehicle, e.g., so the vehicle can navigate relative to the objects. First radar data, e.g., from a first radar sensor, and second radar data, e.g., from a second radar sensor, can be analyzed to determine returns representing an object. The returns can then be used to determine a yaw rate and/or a two-dimensional velocity of the object. In some examples, differences in time between sensor data collection can be corrected/compensated based on previous (historical) tracked object information to provide better estimates.

Techniques for allowing a vehicle equipped with at least one radar to take-off and land using radar return images of a landing site. The at least one radar generates radar return image(s) of the landing site, specifically of reflective symbols attached to the landing site, allowing the vehicle to orient itself to the landing site and providing information specific to the landing site. Position and velocity in relation to a landing site can be determined using at least one radar and a guidance and landing system. Using the position and velocity information, the guidance and landing system can guide the vehicle to and from the landing site and/or determine whether an obstacle requires the use of an alternate landing site.

A buoy-type high-frequency ground wave radar system. A buoy platform is used as an offshore carrier of a ground wave radar. A sky wave emission subsystem is disposed on a shore base and emits a high-frequency electromagnet wave. After the high-frequency electromagnet wave is refracted by the ionosphere and is reflected by the sea surface, a sky wave signal is formed. An attitude measurement subsystem measures and acquires attitude data of the buoy platform in real time. A ground wave radar subsystem receives a ground wave signal by using the ground wave radar, and processes the signal to form a ground wave doppler spectrum. Simultaneously, the sky wave signal is received, ionosphere disturbance compensation is performed on the sky wave signal in a frequency domain and then the sky wave signal is processed to form a sky wave doppler spectrum. The ground wave radar subsystem reconstructs an actual geographic coordinate system according to the attitude data measured by the attitude measurement subsystem and then the ground wave or the sky wave doppler spectrum is used to inverse wind wave current data in the reconstructed actual geographic coordinate system. The sky wave emission subsystem and the ground wave radar subsystem carry out time synchronization by means of a GPS synchronization networking. The system can detect a sea region of any distance and is suitable for high sea detection.

A system for tracking wearable user devices is provided herein. The system may include a tracking environment, comprising: one or more scene light sources, wherein the location of the scene light sources is known within said tracking environment; one or more scene detectors operable to detect light within the tracking environment, wherein the location and orientation of said one or more scene detectors is known within said tracking environment; one or more scene reflectors operable to reflect light originating from said one or more scene light sources, wherein the location of said one or more scene reflectors is known within said tracking environment; and, one or more wearable user devices comprising a curved reflective surface with known geometry; and, a computer processor operable to analyse light readings detected by said one or more scene detectors, and to calculate a position of the one or more wearable user devices.