Diagonal Loading for STAP and Its Performance Analysis

For the moving target detection with space-time adaptive processing (STAP), the non- homogeneity will cause the covariance matrix estimation error, which substantially results in the STAP performance degradation. Diagonal loading has long been used as a means to improve the robustness of the spatial filter against mismatches in both the desired spatial signature and the spatial correlation matrix. In this paper, we consider the application of diagonal loading to improve the detection performance for STAP, especially for the covariance matrix mismatch (statistical mismatch) in STAP, namely, there is a mismatch between the actual covariance matrix of interest and the presumed one. For the diagonal loading, the key problem is the choice of the loading level, and the method for selecting the loading level is given, and the particular performance analysis indicates that the diagonal loading can improve the detection probability and the output signal-to-noise ratio. Numerical simulations attest the validity of the analysis.