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With the development of autonomous driving technology, automotive radar hasreceived unprecedented attention due to its day-and-night and all-weatherworking capability. It is worthwhile to note that more and more vehicles areequipped with automotive radars, resulting in mutual interference betweenradars. The interference reduces radar target detection performance, makingperception information unreliable. In this paper, a novel interferencemitigation method based on power-weighted Hough transform is proposed forsolving the radar mutual interference and improving the safety of autonomousdriving systems. Firstly, the frequency modulation characteristics ofinterference signals and target echo signals are analyzed, and differencesbetween the two signals are introduced. Secondly, based on the straight linedetection technique, the power of the mutual interference signal intime-frequency domain is accumulated, and the accurate position of theinterference is located. Finally, the target echo is recovered byautoregressive model. Compared with existing state-of-the-art methods, theproposed method has the ability to retain more useful signals after theinterference mitigation, and achieve better interference detection robustnessunder low signal-to-noise ratio conditions. Simulation experiments and realscenario experiments verify the effectiveness of the proposed method and showits superiority.

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