Abstract: Ghost Object Identification For Automobile Radar Tracking A method of classifying an object detected by a radar device (R) includes identifying two dynamic objects (O) and one stationary object from sensor data detected by at least one sensor; determining a plurality of confidences based on a comparison of the separation distance between each object and a range of each object to the sensor. The method also determining a highest confidence value among them; comparing the highest confidence to a p re-defined threshold; and increasing a corresponding ghost probability, when the highest confidence value is higher than a predetermined threshold or decreasing the corresponding ghost probability, when the highest confidence value is not higher than the predetermined threshold.

Abstract: One or more embodiments of the present disclosure relate to identifying reference portions corresponding to a bounding shape that corresponds to an object. Additionally, the reference portions may include a first reference edge, a second reference edge, and a reference where the first reference edge and the second reference edge intersect. In some embodiments, operations may further include obtaining a first state estimate corresponding to the object and receiving first sensor data corresponding to a first portion of the object, the first sensor data including a first position measurement. Further, operations may further include determining that the first position measurement corresponds to a first reference portion that is one of the reference portions corresponding to the bounding shape and determining a first expected position corresponding to the first portion based at least on the first reference portion.

Abstract: One or more embodiments of the present disclosure relate to obtaining a first state estimate corresponding to an object, the first state estimate including a first velocity vector estimate corresponding to the object. The disclosure may further relate to receiving first sensor data corresponding to a first portion of the object. The embodiments may further include determining a first expected measurement corresponding to the first portion, the first expected measurement including a first expected range rate determined based at least on the first angle measurement and the first velocity vector estimate of the first state estimate. And, determining a second state estimate corresponding to the object, the second state estimate including a second velocity vector estimate corresponding to the object and determined based at least on the first range rate measurement and the first expected range rate.

Abstract: A method and system are disclosed for determining a trailer angle between a vehicle and a trailer attached to a the vehicle. The method includes receiving camera data from a camera supported by a rear portion of the vehicle, left radar data from a left short-range radar supported by a left rear portion of the vehicle, and right radar data from a right short-range radar supported by a right rear portion of the vehicle. A trailer angle is estimated based on the camera data, the left radar data, and the right radar data. The estimated trailer angle is sent to one or more vehicle systems associated with the vehicle.

Abstract: Ghost Object Identification For Automobile Radar Tracking A method of classifying an object detected by a radar device (R) includes identifying two dynamic objects (O) and one stationary object from sensor data detected by at least one sensor; determining a plurality of confidences based on a comparison of the separation distance between each object and a range of each object to the sensor. The method also determining a highest confidence value among them; comparing the highest confidence to a p re-defined threshold; and increasing a corresponding ghost probability, when the highest confidence value is higher than a predetermined threshold or decreasing the corresponding ghost probability, when the highest confidence value is not higher than the predetermined threshold.