协方差矩阵结构的广义杂波分组估计方法

针对球不变随机向量建模的相关复合高斯杂波背景下雷达目标自适应检测的协方差矩阵结构估计问题，将均匀杂波分组方法进行推广和改进，提出了杂波协方差矩阵结构的广义迭代杂波分组估计（GRCCE）方法。首先，在广义杂波分组背景下利用最大似然方法推导了协方差矩阵结构估计的迭代过程；其次，基于杂波分组思想，给出了广义杂波分组估计(GCCE)，利用GCCE作为初始化估计矩阵进行迭代，得到协方差矩阵结构的GRCCE；最后，通过仿真对方法的有效性进行了检测，结果表明，GRCCE只需要一次迭代就能达到收敛，估计精度随着杂波一阶相关系数的增大而提高，而不受纹理分量参数变化的影响。与现有方法相比GRCCE适应杂波环境更广，估计精度更高，而且计算量更小。

Generalized Clutter Clustered Estimation of Covariance Matrix Structure#br#

The problem of covariance matrix structure estimation is addressed for radar target adaptive detection in correlated compound Gaussian clutter environment modeled as spherically invariant random vector. The method of clutter clustered estimation is generalized and modified, and a generalized recursive clutter clustered estimation (GRCCE) is proposed. The recursive process of covariance matrix structure estimation is derived in generalized clutter clustered environment based on the method of maximum likelihood estimation. A generalized clutter clustered estimation (GCCE) is proposed based on the idea of clutter clustered estimation. And then GRCCE is obtained by recursion with GCCE as the initialized estimation matrix. The simulation results show that one recursion is sufficient to obtain the desired goals. The estimation accuracy of the GRCCE is improved as first order correlation coefficient becomes bigger, and it is independent of the clutter texture components. Compared with the existing methods, the GRCCE is shown to be better adaptability, higher estimation accuracy and lower computational burden.