A Grating-Lobes Suppression Method for Distributed MIMO Radar Network

Distributed multiple-input multiple-output (MIMO) radar networks are essential for high-resolution sensing applications, yet their sparse array configurations inherently produce grating lobe artifacts that degrade imaging quality. To address these challenges, we propose a grating lobe suppression method that combines digital beamforming (DBF) with zero migration (ZM). By aligning the nulls of subarray beams with grating lobe positions and narrowing the mainlobe through multiapodization (MA) techniques—selecting the minimum response across multiple processed angular offset channels—the method effectively suppresses first-order bilateral grating lobes associated with preset targets. To address the limitation of angle-dependent suppression, a beamspace domain ZM method based on fast 2D discrete-time Fourier transform (DTFT) is proposed. This approach decouples target-specific maximum migration angles from non-uniform angular intervals of beam nulls in the beamspace domain, enabling angle-independent grating lobe suppression across the entire angular spectrum, making it suitable for far-field wide-field-of-view (FOV) scenarios. Furthermore, a pixel-based clean (PC) algorithm resolves coupled grating lobes in multi-target environments by dynamically validating true targets and suppressing residual artifacts. Numerical simulations and experimental results confirm that the method effectively suppresses grating lobes robustly while preserving high resolution and computational efficiency.