Efficient Matrix Sparse Recovery STAP Method Based on Kronecker Transform for BiSAR Sea Clutter Suppression
Junao Li, Zhongyu Li, Qing Yang, Haozhuo Pi, Yahui Wang, Hongyang An, Junjie Wu, Jianyu Yang
Abstract
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. STAP based on sparse recovery (SR-STAP) is an effective method for clutter suppression, but two major problems still remain. (1) The multiple samples for solution need to satisfy the same spatio-temporal distribution characteristics. Nevertheless, such consistency is not applicable when considering violent internal motion of sea clutter. (2) The computational complexity is exceedingly high. To issue these problems, an efficient matrix sparse recovery STAP (MSR-STAP) method based on Kronecker transform is proposed. The proposed method mainly consists of three steps: (1) Generalized Keystone transform in preprocessing stage is used for RCM correction and DFM compensation. (2) Multiple spatio-temporal samples acquisition strategy for CUT is designed, to enhance the solution robustness. (3) An efficient MSR-STAP model is established and solved. Subsequently, the space-time filter is designed without clutter covariance matrix estimation, to facilitate effective sea clutter suppression. Compared with existing SR-STAP methods, computational complexity of the proposed method decreases by orders of magnitude, and the spatio-temporal spectrum expansion effect is greatly reduced. The sea clutter suppression performance is verified with numerical simulations.