Robust FDA-STAP Approach Based on Multiple Response Constraints

Abstract Frequency diverse array (FDA) has the ability to suppress the range-dependent interference and resolve the range ambiguity by using its additional degree-of-freedom (DOFs) in range domain. However, the spatial-temporal spectrum of fast-moving target is not ideally focused in spatial-temporal plane, which causes a large mismatch between the real and presumed target locations and significantly degrades the performance of space-time adaptive processing (STAP). To solve this problem, in this paper, a robust FDA-STAP approach based on multiple magnitude response constraints is proposed to improve the detection performance of fast-moving target. Specifically, several small uncertainty sets are employed to constraint the magnitude response, and then the worst-case based optimization problem is formed. To reduce the influence of the spatial-temporal-spectrum-defocusing of fast-moving target, a non-focused constraint on the STAP weight vector is devised. Finally, the proposed method is formulated as a non-convex quadratically constrained quadratic programming (QCQP) problem, which is efficiently resolved by using multiple constraints relaxation technique. Simulation results demonstrate that the proposed method outperforms other state-of-the-arts methods including well-controlled mainbeam and superior target detection performance.