Abstract

Millimeter-wave radars are widely used in automotive radars because of their all-weather and all-day operation capability. However, as more and more radar sensors are used, the possibility of mutual interference between radars increases dramatically. Severe interference increases the noise level, affects target detection performance, and can lead to missed detection and wrong detection. In this study, a novel solution to the problem of mutual radar interference is introduced. The method is based on the analysis and synthesis of spectrum sub-bands. Specifically, the received radar signal is partitioned into sub-bands, after which interference mitigation is carried out in each sub-band. Finally, the signals are reconstructed to obtain interference-free data. The effectiveness of this approach is evaluated using both a simulated multi-target scenario and a real-life experimental environment. The results demonstrate that the proposed method outperforms existing techniques in terms of interference mitigation while exhibiting rapid processing speeds.

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