A sparse moving array imaging approach for FMCW radar with dual-aperture adaptive azimuth ambiguity suppression and adaptive QR decomposition

Range-azimuth imaging of ground targets via frequency-modulated continuous wave (FMCW) radar is crucial for effective target detection. However, when the pitch of the moving array constructed during motion exceeds the physical array aperture, azimuth ambiguity occurs, making range-azimuth imaging on a moving platform challenging. To address this issue, we theoretically analyze azimuth ambiguity generation in sparse motion arrays and propose a dual-aperture adaptive processing (DAAP) method for suppressing azimuth ambiguity. This method combines spatial multiple-input multiple-output (MIMO) arrays with sparse motion arrays to achieve high-resolution range-azimuth imaging. In addition, an adaptive QR decomposition denoising method for sparse array signals based on iterative low-rank matrix approximation (LRMA) and regularized QR is proposed to preprocess sparse motion array signals. Simulations and experiments show that on a two-transmitter-four-receiver array, the signal-to-noise ratio (SNR) of the sparse motion array signal after noise suppression via adaptive QR decomposition can exceed 0 dB, and the azimuth ambiguity signal ratio (AASR) can be reduced to below −20 dB.