基于相对距离准则的STAP协方差矩阵估计算法

Covariance matrix estimation for STAP based on relative distance criterion

针对杂波功率依距离缓变的非均匀环境,提出了基于相对距离准则的加权协方差矩阵估计算法。通过对加权最大似然估计概念的描述和原始问题的公式化,在相对距离准则下设计加权函数,使得在样本矩阵求逆(SMI)检测器的条件下,检测算法的相对距离达到最大,并给出了实用的近似加权系数求解方法。通过性能分析可知,在相对距离最大条件下估计的协方差矩阵的条件信杂噪比损失同时达到最大。最后的仿真分析也验证了该算法的正确性和有效性。

For the clutter power slowly changed environment-range-dependent nonhomogeneity, the weighting covariance matrix estimation algorithm is proposed which is based on the relative distance criterion. By the description of the weighting maximal likelihood estimation and its formulation, and based on the relative distance criterion, the weighting function is designed. Via the maximum of the relative distance criterion of the sample matrix inversion detector, the practical approximately solution to the weighting function is given. From the performance analysis, the maximum of the conditional SCNR loss is equivalent to the maximum of the relative distance criterion when the optimal weighting function is applied. At last, the simulation results attest the correctness and the validity of the proposed algorithm.