As an important remote sensing technology, millimeter-wave radar is used for environmental sensing in many fields due to its advantages of all-day, all-weather operation. With the increasing use of radars, inter-radar interference becomes increasingly critical. Severe mutual interference degrades radar signal quality and affects the performance of post-processing, e.g., synthetic aperture radar (SAR) imaging and target tracking. Aiming to deal with mutual interference, we propose an interference mitigation method based on variational modal decomposition (VMD). With the characteristics that the target is a single-frequency sine wave and the interference is a broadband signal, VMD is used for decomposing the radar received signal and separating the target from the interference. Interference mitigation is then implemented in each decomposed mode, and an interference-free signal is obtained through the reconstruction process. Simulation results of multi-target scenarios demonstrate that the proposed method outperforms existing decomposition-based methods. This conclusion is also confirmed by the experimental results on real data.
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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