机载雷达三维空时两级降维自适应处理

该文研究了机载雷达3维空时自适应处理(3D-STAP)方法,并结合先时后空的自适应处理(mDT-SAP)结构提出了一种新的空时两级降维准最优技术。该方法首先采用固定结构的时域多普勒预处理降低杂波时域相关性,然后基于2维空域的可分离性构造出两个低维的俯仰和方位向权值,最后结合双迭代算法进行循环求解。理论分析与仿真结果表明,该文所提方法与传统方法相比具有运算量小、收敛性强、所需训练样本少的优点,并拥有优良的杂波抑制性能和较强的误差鲁棒性,有利于工程化实现。

Three-dimensional Spatial-temporal Two-step Dimension-reduced Adaptive Processing for Airborne Radar

Three-dimensional Space-Time Adaptive Processor (3D-STAP) is studied in this paper for airborne radar system, and a new kind of two-step dimension-reduced suboptimum STAP technique is proposed based on the frame of pre-Doppler followed by spatial adaptive processing (mDT-SAP). The Doppler filter with fixed configuration is performed on each spatially sampled element to reduce the correlation in the temporal domain, followed by spatial bi-iterative adaptive processing on the azimuth and elevation of the platform array based on the two separable weight vectors. It is shown that the proposed method has lower the computation load and needs smaller training data size compared to the traditional method. In additional, the effectiveness and robustness of the proposed method are demonstrated via numerical experiment.