Matrix Sparse Model Based Spatio-Temporal Spectrum Recovery Method for Bisar Sea Clutter Suppression

Sea clutter suppression plays a crucial role in maritime moving target indication. However, in the bistatic SAR (BiSAR) system, traditional space-time adaptive processing (STAP) method can't satisfy the expected performance due to severe range cell migration (RCM), Doppler frequency migration (DFM), nonstationary clutter, and spatio-temporal spectrum expansion caused by the internal motion of sea clutter. To issue these problems, a matrix sparse model based spatio-temporal spectrum recovery method is proposed. The proposed method mainly consists of three steps. Firstly, Generalized Keystone transform in preprocessing stage is used for RCM correction and DFM compensation. Then, multiple spatio-temporal samples acquisition strategy for cell under test is designed, to enhance the solution robustness. Next, a matrix sparse model for BiSAR spatio-temporal spectrum recovery is constructed and solved. Finally, the sea clutter suppression performance is verified with numerical simulations.