STUDY ON KNOWLEDGE-AIDED REDUCED RANK STAP METHOD

摘要

A novel knowledge-aided reduced rank (RR) space-time adaptive processing (STAP) method is presented in this paper. Firstly, a clutter model is constructed by priori knowledge such as flying parameters, radar system parameters, mapping and terrain parameters. Secondly, the clutter is performed via the pre-whiten processing of the constructed clutter model. Finally, RR STAP method is used to suppress the residual clutter. The simulation result shows the KA-RR method has better robustness in non-homogeneous clutter environment compared with conventional RR STAP method.