Adaptive detection of moving targets in sea clutter environment is considered as one of the crucial tasks for radar seekers. Due to the severe spreading of the sea clutter spectrum, the ability of space-time adaptive processing with sum and difference beams (S?-STAP) algorithms to suppress the sea clutter is very limited. This paper, investigated the low-rank property of the range-Doppler data matrix according to the eigenvalue distribution from the eigen spectrum, and proposed an efficient S?-STAP detector based on the robust principle component analysis (RPCA) algorithm to detect moving targets, which meets the low-rank matrix recovery conditions. The proposed algorithm first adopts S?-STAP algorithm to preprocess the sea clutter, then separates the sparse matrix of target component from the range-Doppler data matrix through the RPCA algorithm, and finally, effectively detects moving targets in the range-Doppler plane. Simulation results demonstrate the effectiveness and robustness of the proposed algorithm in the low signal-to-noise ratio scenarios.
- Accelerated proximal gradient
- Low-rank matrix recovery
- Principal component analysis
- Space-time adaptive processing