基于奇异协方差矩阵的谱估计方法  

Spectral estimator with rank-deficient covariance matrix

作　　者：苏志刚[1] 彭应宁[1] 吴仁彪[2] 

机构地区：[1]清华大学电子工程系,北京100084 [2]中国民航大学智能信号与图像处理天津市重点实验室,天津300300

出　　处：《清华大学学报（自然科学版）》2008年第1期55-58,共4页Journal of Tsinghua University(Science and Technology)

基　　金：国家自然科学基金资助项目(60325102,60428101);教育部科技创新工程重大项目培育资金资助项目(706004);高等学校博士学科点专项科研基金资助项目(20060003101);中国博士后科学基金资助项目(20060390484)

摘　　要：为了解决秩亏RCF(robust Capon filter-bank)谱估计方法的估计性能不稳健问题,提出一种基于奇异协方差矩阵的谱估计方法。该方法根据空间约束和导向矢量误差约束获得相应的窄带滤波器,并利用其对Capon滤波矢量进行滤波得到谱估计。仿真结果表明:在采样协方差矩阵奇异的情况下,该谱估计方法获得的谱估计在精度及分辨率上均明显优于秩亏RCF谱估计方法。该方法是一种可以利用少量快拍进行谱估计的有效方法。A spectral estimator based on the rank-deficient sample covariance matrix was developed to improve the robustness of estimates of the rank-deficient robust Capon filter-bank （RCF） spectral estimator. The estimator utilizes constraints on both the subspace and the errors of steering vectors to design a narrow filter. The filter outputs the spectral estimate with the filtering vector as its input. The filtering vector is formed by weighting snapshots with the Capon weight. Simulation results for a singular sample covariance matrix show that the spectral estimator obtains the spectral estimates with better accuracy and resolution than the rank-deficient RCF spectral estimator. Thus the estimator is an efficient estimator which utilizes only a few snapshots to estimate the spectrum.

关 键 词：雷达数据处理 谱估计 匹配滤波 

分 类 号：TN957.52[电子电信—信号与信息处理]