A dimension-reduced STAP method for airborne bistatic radar based on time-varying weighting techniques

This paper introduces a novel dimension-reduced space-time adaptive processing (STAP) method to deal with the problem of low performance of clutter suppression using the traditional dimension-reduced STAP method in the airborne bistatic radar system. In order to compensate the clutter range dependence of the airborne bistatic radar, this method uses the time-Varying weighting(TVW) techniques to modify the error of the dimension-reduced covariance matrix of clutter and noise caused by the nonlinearity. The theoretical analysis and simulation results manifest that this method can solve effectively the clutter nonhomogeneity of the airborne bistatic radar in different configure situations. Compared with the linear time-Varying weighting, this method can reduce the computational load and training cells. This method is also a data-independent method which can adaptively compensate the range nonstationarity without the prior knowledge of the moving platforms and varying scenarios.