海杂波协方差矩阵估计及其对目标检测性能的影响

摘要

In the problem of the useful signal detection in sea clutter, the reference data are used for the estimation of the clutter covariance matrix. Different covariant matrix estimators result in different signal detection performances. The several covariant matrix estimators are given, such as sample covariance matrix, normalized sample covariance matrix, maximum likelihood estimator, approximated maximum likelihood estimator. The non-Gaussian and non stationary of sea clutter are analyzed secondly. In the end, the impact of different covariance matrix estimators on the signal detection performance is analyzed using the normalized matched filter as the signal detector. The results show that the detection performance using simulated data is better than that using measured data because of the non-stationary of sea clutter. And the detection performance using the maximum likelihood estimator of clutter covariance matrixes is better than those using other estimators.%在海杂波中检测有用信号,杂波的协方差矩阵需要利用参考数据进行估计,不同的估计方法对信号的检测性能产生不同的影响.首先,给出了几种杂波协方差矩阵估计,即样本协方差矩阵、正则化样本协方差矩阵、最大似然估计和渐进最大似然估计；然后,分析了海杂波数据的非高斯性和非平稳性；最后,利用正则化匹配滤波器作为信号检测器,分析了不同协方差估计对检测性能的影响.分析结果表明,由于实测数据的非平稳性,检测性能均比仿真数据获得的检测性能要差.而将杂波协方差矩阵的最大似然估计应用于检测器,能够获得较好的检测性能.