Fast 3-D Near-Field Imaging Algorithm for Quasi-Coherent MIMO-SAR

Quasi-coherent radar imaging systems have gained attention for their low hardware complexity, design flexibility, and potential aperture scalability. However, the use of independent phase-locked loop (PLL) to generate local oscillator (LO) signals for each subarray introduces inter-subarray phase deviations, which limit the effectiveness of multistatic range migration algorithm (RMA) reliant on inter-subarray signal coherence. To address this issue, we propose an imaging algorithm based on multilevel FFT decomposition that relies solely on intra-subarray data, and provide two specific implementation forms. The one divides the entire array into subarrays, applies zero-padding and FFT to align their wavenumber domains for summation, and finally reconstructs images through dimension reduction and inverse fast Fourier transform (IFFT). To improve generality, an alternative implementation uses nonuniform fast Fourier transform (NUFFT) for domain alignment, extending the algorithm to MIMO arrays with arbitrary topologies. Simulations and experiments are carried out for verification, and the proposed algorithm is compared with the back projection algorithm (BPA) and monostatic RMA based on range compensation. The results demonstrate the effectiveness of the proposed algorithm for imaging and its superiority in imaging quality and computational efficiency.