Estimation of Moving Direction and Size of Vehicle in High-Resolution Automotive Radar System

Abstract

In this paper, we propose methods to estimate the moving direction and size of a target vehicle based on point cloud data detected by high-resolution automotive radar sensor. Previous studies using automotive radar sensors have proposed methods to roughly estimate the moving direction of vehicles, such as left, straight, or right. This study proposes methods to estimate not only the specific moving direction but also the approximate size of the vehicle. First, we use the high-resolution frequency-modulated continuous wave radar to acquire point cloud data for vehicles moving at various angles. In the point cloud data, radar signals are strongly reflected from the side of the vehicle and detected as a line segment. The proposed moving direction and size estimation method is based on line segment extracted from the Hough transform (HT). To extract the line segment from the point cloud data, the Hough transform is used. Using the extracted line segment, methods for estimating the moving direction and size of the vehicle are proposed. And then, the quick hull algorithm is used to estimate the center point of the vehicle to match the position of the target in the coordinate system. Finally, the direction, width, and length of the vehicle estimated from the proposed methods show average errors of 1.94<inline-formula> <tex-math notation=LaTeX>$^\circ$</tex-math> </inline-formula>, 4.32%, and 6.32%, respectively. In addition, when compared to the conventional principal component analysis (PCA)-based method, our proposed method exhibits superior performance in terms of estimation accuracy. Moreover, we have validated the effectiveness of the proposed method even in scenarios with multiple vehicles and in noisy road environments. IEEE