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Interference is mitigated by reconstructing the received signal via fast-or slow-time AR models estimated using the clean samples.

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Millimeter-wave (mm-wave) frequency modulated continuous wave (FMCW) radars are increasingly being deployed for scenario perception in various applications. It is expected that the mutual interference between such radars will soon become a significant problem. Therefore, to maintain the reliability of the radar measurements, there must be procedures in place to mitigate this interference. This paper proposes a novel interference mitigation technique that utilizes the pulse compression principle for interference compression and mitigation. The interference in the received time-domain signal is compressed using an estimated matched filter. Afterwards, the compressed interference is discarded, and the signal is repaired in the pulse-compressed domain using an autoregressive (AR) model. Since the interference spans fewer samples after compression, the signal can be restored more accurately in the compressed domain. Real outdoor measurements show that the interference is effectively suppressed down to the noise floor using the proposed scheme. A signal to interference and noise ratio (SINR) gain of approximately 14 dB was achieved in the experimental data supporting this study. Moreover, the results indicate that this method is also applicable to situations where multiple interference sources are present.