Automotive Radar Mutual Interference Mitigation Based on Hough Transform in Time-Frequency Domain

TL;DR

This paper introduces a novel interference mitigation method for automotive radars using a power-weighted Hough transform in the time-frequency domain, enhancing detection robustness and signal recovery in autonomous driving systems.

Contribution

It proposes a new interference mitigation technique based on Hough transform that improves detection accuracy and signal retention compared to existing methods.

Findings

Better interference detection robustness under low SNR

More effective recovery of target echoes

Enhanced safety in autonomous driving systems

Abstract

With the development of autonomous driving technology, automotive radar has received unprecedented attention due to its day-and-night and all-weather working capability. It is worthwhile to note that more and more vehicles are equipped with automotive radars, resulting in mutual interference between radars. The interference reduces radar target detection performance, making perception information unreliable. In this paper, a novel interference mitigation method based on power-weighted Hough transform is proposed for solving the radar mutual interference and improving the safety of autonomous driving systems. Firstly, the frequency modulation characteristics of interference signals and target echo signals are analyzed, and differences between the two signals are introduced. Secondly, based on the straight line detection technique, the power of the mutual interference signal in time-frequency domain is accumulated, and the accurate position of the interference is located. Finally, the target echo is recovered by autoregressive model. Compared with existing state-of-the-art methods, the proposed method has the ability to retain more useful signals after the interference mitigation, and achieve better interference detection robustness under low signal-to-noise ratio conditions. Simulation experiments and real scenario experiments verify the effectiveness of the proposed method and show its superiority.