A Grating Lobes Suppression Method for MIMO Imaging Radar Based on Phase-Coherence-Guided Adaptive Threshold Classification

The sparse array configuration of multi-input multi-output imaging radar leads to high grating lobes problem in the imaging process, which significantly degrades final image quality. Although the traditional Phase Coherence Factor can partially mitigate these grating lobes, it suffers from limitations such as attenuation of the main lobe energy. To overcome these drawbacks, this paper proposes a novel grating lobes suppression method based on phase-coherence-guided adaptive threshold classification. This method first adaptively determines a classification threshold by analyzing the phase coherence features of the target main lobe. Using this threshold, all the grids in the radar image are classified into two categories and distinct schemes are applied to compute their respective weighting factors. Finally, grating lobes in the image are suppressed by weighting the original radar image. Numerical simulation and field experiment both confirm the effectiveness of the proposed method, which achieves a higher peak sidelobe ratio than conventional methods, demonstrating promising practical value.