Mutual Interference Suppression Using Wavelet Denoising in Automotive FMCW Radar Systems

摘要

This paper presents an efficient mutual interference suppression method using wavelet denoising in automotive radar systems. When a radar signal transmitted from another radar-equipped vehicle flows into our radar system, it acts as an interference signal and degrades the target detection performance. With wavelet denoising, the interference signal can be extracted from the time-domain low-pass filter output. Then, the effect of the interference can be mitigated by subtracting the interference signal from the original low-pass filter output. As a result, the beat frequency containing the target information can be estimated accurately. Simulation results show that the proposed method can enhance the estimation accuracy of the target's distance, velocity, and angle. In addition, the performance of the proposed method is verified through actual experiments using heterogeneous radars. In the measurement results, even though the exact specifications of the radar signal transmitted from the other vehicle are not identified, the interference is effectively suppressed. Unlike other existing methods, the proposed method using wavelet denoising does not need to generate a specific radar waveform and it can mitigate interference only by signal processing without changing the existing hardware.