Trailer angle estimation using radar point clouds

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Department of Electrical and Computer Engineering; Department of Applied Computing


Algorithms for trailer control and backup need to keep track of the trailer angle, therefore, the angle needs to be determined. This work shows that the angle can be estimated using 2D point clouds collected from two automotive radars installed in the taillight fixtures of a trailer-coupled truck. The detection threshold of each radar is reduced to allow more detections of the trailer. A tracking procedure is introduced to find the trailer detections as the trailer rotates; the tracked set of detections are then compared with one or more reference sets to estimate the angle. Estimated angles are further refined with a Kalman filter to obtain smooth estimates of the angle. The algorithm is tested on 15 datasets; each dataset is obtained in an experiment in which the trailer is rotated up to about 40∘ in both radar directions. The estimates from all the datasets result in a global root mean squared error of about 0.9∘ for up to 10∘ absolute trailer rotation; about 1.3∘ for up to 20∘ absolute rotation; about 1.5∘ for up to 30∘ absolute rotation; and about 1.9∘ for all trailer angles considered. The algorithm executes in about 3 ms on a typical personal computer.

Publication Title

Signal Processing