空域分解的机载MIMO雷达空时处理方法

摘要

Compared with the traditional airbome phased-array radar,the ability for clutter suppression and moving target detection of space-time adaptive processing in the airborne multiple-input multiple-output radar (MIMO-STAP) can be greatly improved.However,the huge computational cost and training sample requirement limit its practical application.In order to solve this problem,we proposed the post-Doppler adaptive processing method based on the multi-stage spatial decomposition in airborne MIMO radar.This method decomposed the post-Doppler adaptive weight vector into the Kronecker product of several short weight vectors.Then the cyclic iteration was applied to solve the desired weight vector.The simulation experiments showed that this method had the advantage of fast convergence.Its performance is evidently superior to the traditional post-Doppler processing method especially in large-scale antenna array radar.%相对于传统机载相控阵雷达,应用于机载多输入多输出雷达中的空时自适应处理(MIMO-STAP)技术可以获得杂波抑制和动目标检测能力的大幅提升.但是传统MIMO-STAP所需要的计算量和样本需求量巨大,无法满足实际处理要求.为了解决这一问题,我们提出了一种基于空域多级分解的机载MIMO雷达后多普勒自适应方法.该方法将后多普勒自适应权系数进行分解,使其变为几个短向量的Kronecker乘积,然后利用循环迭代的思想求解自适应权.实验表明该方法具有快速收敛性,在小样本大阵列条件下该方法明显优于传统的后多普勒处理方法.