Time-frequency-sparsity-based interference mitigation using order statistics for automotive radar

Recently, radar has been massively applied in driver assistance and autonomous driving system. However, radars in traffic may interfere each other, leading to decreased detection sensitivity or ghost targets. Over the past decades, there are multiple approaches proposed to solve this problem. In this work, we propose a sparsity-based method to mitigate the interference in the so-called time-frequency-slow-time (TFS) domain using order statistics for the first time. We evaluate and compare the performance of the proposed method with existing signal processing-based methods.