Robust STAP Against Unknown Mutual Coupling Based on Middle Subarray Clutter Covariance Matrix Reconstruction

Abstract

The presence of mutual coupling usually causes space-time steering vector distortion for space-time adaptive processing (STAP) in airborne radar, thereby causing significant performance degradation. In this paper, a robust STAP approach was proposed against mutual coupling based on middle subarray clutter covariance matrix reconstruction. To address the space-time steering vector distortion caused by the mutual coupling, the training snapshots of middle subarray were obtained using the spatial-temporal selection matrix, and they were collected to compute the sample covariance matrix (SCM). Thus, the clutter-plus-noise covariance matrix (CNCM) of middle subarray was reconstructed by utilizing the clutter Capon spectrum of middle subarray to integrate over the possible clutter spatial-temporal domain. Moreover, the target covariance matrix of middle subarray was calculated by employing the target Capon spectrum of middle subarray to integrate over the possible target region, and the space-time steering vector of the target was estimated with the eigenvector corresponding to its maximum eigenvalue. Finally, the proposed robust STAP weight vector of middle subarray was built. The proposed method is capable of simultaneously mitigating the mutual coupling, target components in the SCM, and target space-time steering vector mismatch. The simulation results verified the effectiveness of the proposed approach.