Improved Dimension-Reduced Structures of 3D-STAP on Nonstationary Clutter Suppression for Space-Based Early Warning Radar

Abstract

By introducing degrees of freedom (DOFs) in elevation, the elevation-azimuth-Doppler three-dimensional space–time adaptive processing (3D-STAP) methods have better performance when suppressing the nonstationary clutter caused by the Earth’s rotation in space-based early warning radar (SBEWR). However, the 3D-STAP methods use much more auxiliary beams, leading to greater demands on the training samples and heavier computational burdens than the conventional STAP methods. To solve this problem, the ideas of sum–difference beams, generalized multiple beams and Doppler-domain localization are applied here, and three improved dimension-reduced structures of 3D-STAP are proposed in this article. After analyzing the characteristics and distribution of nonstationary clutter for SBEWR, we find that the demands for auxiliary beams are different in elevation, azimuth and Doppler dimension. In addition, the suggestion to choose the number of auxiliary beams in each dimension is given. Simulation experiments are conducted to verify the analysis and evaluate the performance of the proposed methods. The simulation results show that the proposed 3D-STAP methods have better performance and lower computational burdens than typical 3D-STAP methods.