Imaging Performance Improvement for Multistatic SAR Based on Wavenumber Spectrum Trimming

Multistatic synthetic aperture radar (MuSAR) has the capabilities of short-time high resolution imaging and multi-angle target observation. The imaging quality of coherent MuSAR depends on the distribution of wavenumber spectrum (WS). In this paper, an imaging performance improvement method based on WS trimming is proposed to obtain high-quality imaging results when the WS distribution is not ideal. First, the echo signals of MuSAR are derived. Then, the distribution of the WS is analyzed, and the WS trimming problem is transformed into a constrained multiple objective optimization problem (CMOP), which is optimally solved by multi-objective particle swarm optimization (MOPSO) algorithm. Finally, numerical simulation are performed to verify the effectiveness of the proposed method.