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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 (ΣΔ-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 ΣΔ-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 ΣΔ-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. [ABSTRACT FROM AUTHOR]

A novel space-time adaptive processor based on variable diagonal loading is proposed. On the basis of analysis of constraint equations, the actual space-time steering vectors of the desired signal can be solved using the Lagrange multiplier methodology. The optimum weight vector of space-time beamforming algorithm can be calculated. And the amount of diagonal loading can be precisely calculated based on the uncertainty set of the space-time steering vectors. Results of computer simulation verify the efficiency of the proposed algorithm. [ABSTRACT FROM AUTHOR]