Radar and LiDAR sensors play important roles in autonomous vehicles and ADAS (advanced driving assistance systems) in automobiles, however, they can only detect objects in view (line-of-sight). For example, when three vehicles are driving on road in a same lane, and if the first vehicle suddenly brakes, the third vehicle cannot detect it by regular radar and/or LiDAR because the second vehicle in front blocks the view. This invention discloses system and method to enable radar and/or LiDAR to detect vehicles on road that are blocked in view by another vehicle by specially configured active beacon transmitters, and reduce risks of rear-end collisions.

Exemplary system, method and computer-accessible medium for selecting at least one location of (i) at least one receiver or transceiver or (ii) at least one transmitter or transceiver can be provided. For example, it is possible to facilitate a receipt, from the at least one transmitter or transceiver, of a plurality of signals by the receiver(s) or transceiver(s). Each of the signals has a multipath component. Then, it is possible to determine time of flight (ToF) information and angle of arrival (AoA) information of the multipath components present in the signals. Further, it is possible to determine one or more possible locations of (i) the receiver(s) or transceiver(s) or (ii) the transmitter(s) or transceiver(s) based on the ToF information, the AoA information, and a model of physical surroundings. The location(s) of (i) the receiver(s) or transceiver(s), or (ii) the transmitter(s) or transceiver(s) can be selected based on the one or more possible locations.

A driving assistance device includes an object detection unit, an acquisition unit acquiring a first value of a relative speed of an approaching object with respect to an own vehicle, a ghost determination unit, and an assistance determination unit. The ghost determination unit calculates a second value of the relative speed of the approaching object in accordance with a speed of the own vehicle and a value of the relative speed of a following object located between the own vehicle and the approaching object; calculates, as a speed difference, an absolute difference between the first value of the relative speed and the second value of the relative speed; calculates, as an azimuth difference, an absolute difference between an azimuth of the following object and an azimuth of the approaching object; and determines whether the approaching object is the ghost target based on the speed difference and the azimuth difference.

One embodiment of the present invention relates to a method for performing a vehicle image reconstruction by a sensing vehicle (SV) in a wireless communication system, the method comprising: receiving a plurality of stepped-frequency-continuous-wave (SFCW) from target vehicle (TV); receiving signature waveforms in a different frequency range for the plurality of SFCWs; performing synchronization by using phase-difference-of-arrival (PDoA) based on the signature waveforms; reconstructing one or more virtual images of the TV; and deriving a real image form the determined one of more Virtual Image.

A vehicle is controlled according to a situation in another lane across an adjacent lane adjacent to a traveling lane. A vehicle control device includes an object detection unit, a relative relationship information calculation unit, and a vehicle control unit. The object detection unit is installed on a vehicle of an own vehicle. The object detection unit detects an object existing in another lane across an adjacent lane adjacent to a traveling lane in which the vehicle of the own vehicle travels. The relative relationship information calculation unit calculates relative relationship information between the vehicle of the own vehicle and the detected object. The vehicle control unit generates a vehicle control signal for controlling the vehicle of the own vehicle on the basis of the calculated relative relationship information.

Disclosed are methods and systems for environment detection in which a first vehicle detects its vehicle environment with at least one sensor, wherein the first vehicle transmits sensor data of the sensor pertaining to its vehicle environment to an off-board server device; at least one second vehicle with at least one sensor transmits sensor data of the sensor pertaining to its vehicle environment to the off-board server device; the off-board server device merges the transmitted sensor data of the vehicles and generates an environmental model of the vehicle environment of the first vehicle on the basis thereof; the environmental model that is generated is subsequently transmitted by the off-board server device to the first vehicle.

Disclosed are techniques for non-line-of-sight (NLOS) target detection. In an aspect, a source vehicle receives, from a roadside unit (RSU), a notification that the RSU is capable of repeating radar signals transmitted by the source vehicle in NLOS directions from the source vehicle, receives, from an active radar repeater associated with the RSU, radar signals for a radar beam sweep in at least one NLOS direction from the source vehicle, receives an angle of each beam of the radar beam sweep, and performs target object detection based on the radar signals for the at least one NLOS direction and the angle of each beam of the radar beam sweep. Example architectures for the active radar repeater are also disclosed.

Object detection for ranging sensor data may detect objects which are not actually present in the environment. To identify certain of these phantom objects, objects detected in the environment are analyzed to determine whether they are enclosed by another object and if the enclosed object has a distance from the ranging sensor higher than the enclosing object. This may suggest that the enclosing object has a surface or other feature that is sensed as additional depth that manifests as a separate detectable object. These phantom objects are identified and removed from further perception processing.

Techniques are disclosed for determining an object's location by using a Reconfigurable Intelligent Surface (RIS) to aid in RF sensing. Radar techniques can be used in which one or more base stations act as a transmitter and a receiving device acts as a receiver in a bistatic or multi-static radar configuration where an RIS directs signals transmitted by the one or more base stations to the receiving device. By comparing the time a line-of-sight (LOS) signal (redirected to the receiving device by the RIS) is received by the receiving device with that of an echo signal (redirected to the receiving device by the RIS) from a reflection of an RF signal from the object, a position of the object can be determined. Depending on desired functionality, this position can be determined by the receiving device or by a location server or other network entity.

The present disclosure is directed to scanning radar reflector systems, methods, and apparatuses; even more particularly to a system, method, and apparatus for scanning and reflecting a radar beam transmitted by a radar transmitter onboard an aerial vehicle with radar reflectors equipped on unmanned aerial vehicles. The radar reflection system may include one or more unmanned aerial vehicles equipped with a one or more axis gimbal upon which a radar reflector is mounted. A user may position the unmanned aerial vehicle and the radar reflector to target a specific region for radar scanning.