Study Of Space-Time Adaptive Processing Approach For Airborne Radar

With the ability of suppressing clutter effectively and improving the detection performance of airborne phased radar greatly, the technique of Space-time Adaptive Processing (STAP) has been researched for more than 30 years at home and abroad. The optimum full rank STAP has not found any application in the real world for its huge computation load, its great implementation complexity, and the difficulty to obtain enough samples to estimate the covariance matrix because of nonhomogeneous characteristics of the airborne radar clutter. The good performance and the difficulty to implement of the optimum full rank STAP give the birth to the reduced-rank(R-R) algorithms, many of which can be used in real time processing. Two methods are proposed of grouping subarrays for the process of datum received from large planar arrays, with their valid simulation results compared with that of the equal noise power method and, after the introduction of the theory of the optimum full rank STAP and the Reduced-Rank STAP and several Reduced-Rank STAP algorithms and the research of grouping subarrays of both line and planar arrays. The characteristics of the airborne radar clutter are researched from the variation of the Doppler spectrum with the ranges, the variation of the Doppler spectrum with the angles, and the clutter degrees of freedom. A method and an improved one are proposed to choose the training samples which are independently and identically distributed (iid) for estimating the covariance matrix. The computer simulation validates the methods proposed, and shows that the clutter near the main- beam can be suppressed and the problem of the nonhomogeneous character of the airborne clutter caused by the quick variation of clutter with the range in near range can be solved.