Study on-STAP in Nonhomogeneous Environment Based on Multistage Wiener Filter

In this paper,an efficient and robust -STAP algorithm for moving targets detection in nonhomo- geneous environment is investigated,which is implemented based on Multistage Wiener Filter(MWF).For culling the training data,a two stages hybrid nohomogeneous detection algorithm is proposed.Based on the general sidelobe canceller structure of MWF,the training data can be firstly censored by the mainbeam output and then followed by the Adaptive Power Residual(APR)detection.In addition,the modified Concurrent Block Processing(CBP) is introduced into the -STAP algorithm, which can significantly reduce the computational load. Theoretical analysis and simulation results are presented to demonstrate that, the aforementioned approach can effectively detect the outliers and improve the targets detection performance. This approach has the advantage of fast convergence, low computation load, and good robustness, which is feasible for engineering application.