An Interference Mitigation Technique for Automotive Radar Based on Empirical Wavelet Transform and Maximum Correlation Coefficient

With the development of autonomous driving technology, the probability of mutual interference between automotive radars has significantly increased. Aiming at the increasingly serious mutual interference problem among automotive radars, an interference mitigation technique based on empirical wavelet transform and maximum correlation coefficients is proposed. The technique achieves the reconstruction of clean target signals from interfered original signals by constructing an adaptive wavelet band-pass filter bank, and then locates the target echo signal by the maximum similarity coefficient to achieve the reconstruction of the target echo signal. The effectiveness of this technique has been verified through simulation experiments, and the experimental results show that the proposed technique can significantly reduce the impact of interference. Compared with several existing technologies, it further demonstrates the superiority of the proposed technique.