Research on vehicle track smoothing algorithm for millimeter wave radar detection based on Kalman Filter

Abstract

Millimeter wave radar often suffers from unstable operation of internal components, obstruction interference of external metal plates, large vehicles and other obstacles, and uneven impact of road vehicle target echoes, resulting in abnormal mutation or even false invalidity of vehicle targets in one or more frames. Aiming at the problem of abnormal vehicle target detection due to the impacts of various internal and external factors, this paper proposes a vehicle trajectory smoothing method based on Kalman filter. In this paper, using statistical and analytical methods, the measurement error of vehicle target data detected by millimeter wave radar at intersections is quantized in spatial domain, and the function of vehicle target error measured by radar is obtained. This research algorithm combines the above error function of radar detecting vehicle target with the classical Kalman filtering algorithm, so that the vehicle trajectory can more truly reflect the normal vehicle trajectory. The experimental results show that the algorithm weakens the noise interference of radar data obtained due to the impacts of internal and external factors, greatly improves the accuracy, authenticity and stability of millimeter wave radar, and promotes the development of traffic information analysis and processing.