Interference Suppression and Signal Restoration Using Kalman Filter in Automotive Radar Systems

Abstract

When a radar equipped on an approaching vehicle transmits a signal whose frequency band overlaps with our own radar system, mutual interference problems arise. When mutual interference occurs, the target detection performance is degraded because the target signals are masked by the high power of direct interference signals. Therefore, we propose a signal processing technique to restore signals distorted by mutual interference in an automotive radar system to increase the reliability of target detection. First, since it is necessary to recognize the period where the interference occurred, a method to find the period of interference based on peak detection is presented. Then, the Kalman filter is employed to recover the distorted signal in the interference region by using the undistorted portion of the signal as its input. In simulations using two frequency modulated continuous wave radar systems, the influence of interference was effectively mitigated with our proposed method and target information was correctly estimated.