机载雷达极化空时自适应滤波性能分析

该文针对极化空时自适应处理时，目标极化状态未知的瓶颈问题，提出了先预估计目标的极化状态，然后再进行滤波的方法。该方法无需在极化域专门设置滤波器组进行搜索，大大减少了计算量。提出了最小方差无偏估计和正交投影估计两种极化矢量的估计方法，并将估计性能与Cramer-Rao界进行了比较，从理论上证明了最小方差无偏估计性能较好。与之相对应，提出了两种极化空时自适应滤波方法。仿真验证了特别当目标慢速运动时，极化空时自适应滤波明显优于空时自适应滤波。

Performance Analyse on Polarization-space-time Adaptive Filter in Airborne Radars

Considering the polarization parameters of target are not usually unknown in Polarization Space Time Adaptive Processing(PSTAP),a new method which filters after estimating polarization state is advanced.The new method is deemed to reduce the computation,because which is not using a filter bank to cover the whole polarization domain.Firstly,the Minimum Variance Unbiased(MVU) estimator and Orthogonal Projection(OP) estimator are developed.Then,the Cramer-Rao Bounds(CRB) for MVU estimation of the target polarization parameters are briefly derived.The performance of MVU estimator is superior to OP estimator.Finally,the new PSTAP method performed significantly better than the traditional optimum space-time processing technology,especially in the case of the target slowly moving.Simulations demonstrate the correctness of models.