Automotive radar data filtering approach for Adaptive Cruise Control systems

Abstract

Today automotive radar systems are widely used in automotive safety systems such as adaptive cruise control (ACC). Adaptive cruise control (ACC) automatically maintains the vehicle speed (desired speed) and safe time gap from the vehicle ahead. Automotive radar systems offer the capability to measure simultaneously range and azimuth angle of observed objects inside the observation area. In addition, to achieve accurate and reliable measurement results of the target inside the observation area, the knowledge of target tracking maneuver (preceding vehicle acceleration) is necessary. Many researchers combine the ACC system with other additional hardware such as GPS for radar data correction. In this paper, we used an augmented state space system for preceding vehicle dynamic by taking the acceleration term, as a new state. Then extended Kalman filter (EKF) is applied to the new preceding vehicle system. The positions, relative velocities, and the accelerations of the preceding vehicle are estimated and they are used by the host controller. Hence more accurate data from automotive radar system without using any additional hardware is achieved. In the end, a conventional controller is applied to the system. Simulation results show a very good gap keeping result based on the radar data correction.