Distributed Multi‐MMW Radar Fusion for Target Detection and Tracking in Highway Traffic Environment

Abstract

High‐resolution millimeter‐wave (MMW) radar is viewed as a low‐cost and highly reliable sensor compared to camera, lidar, etc., in moving scenarios and thus has been selected by highway stakeholders as an important roadside detector to detect the movement of traffic vehicles and monitor traffic flow in real time. However, the echo signal of MMW radar in complex highway environment contains not only the signal reflected by target but also spurious signals and other interference signals, which significantly affects the estimation of the target movement state. To solve this problem, an improved vehicle tracking method is designed to simultaneously estimate the polar angle and polar radius in coordinator of MMW radar. Moreover, considering the movement patterns of target vehicles in dynamic uncertain traffic situations, a set of state space models, such as CA, CV, and CT are combined to represent the vehicle movement. In addition, based on the enhanced detection performance of a single radar, the combination of multiple MMW radars’ information was performed to determine the sequential trajectory of the target vehicle on the continuous road sections; then, the historical trajectory of the target vehicle was correlated and fused. Real experiments in highway scenarios show that the method used in this study is effective in deriving the trajectory of the vehicle and improving the positioning accuracy and reliability when the vehicle performs heavy maneuvers.