一种基于子空间分析的快速信源个数估计方法  

A fast source number estimation method based on subspace analysis

作　　者：王晓君[1] 李笑添 WANG Xiaojun;LI Xiaotian(College of Information Science and Engineering,Hebei University of Science and Technology,Shijiazhuang Hebei 050000,China)

机构地区：[1]河北科技大学信息科学与工程学院,河北石家庄050000

出　　处：《太赫兹科学与电子信息学报》2022年第4期366-371,共6页Journal of Terahertz Science and Electronic Information Technology

基　　金：国防科技重点实验室基金资助项目(6142205190401)

摘　　要：针对阵列信号处理中传统信源个数估计方法如基于Akaike信息论准则方法(AIC)、最小描述长度准则方法(MDL)等特征值分解类算法计算量大,且在小快拍数、低信噪比时性能下降甚至无法正确估计的问题,提出了一种基于子空间分析的快速信源个数估计方法。该算法首先利用多级维纳滤波器(MWF)对信号进行快速的子空间估计,然后计算阵列信号协方差在子空间匹配滤波器中的投影值,通过分析其正交性来估计信源个数。研究结果表明,该算法不但在小快拍数、低信噪比时相较于传统特征值分解类算法具有更优异的性能,并且计算量大大降低。Traditional algorithms based on eigenvalue decomposition such as Akaike Information Theory(AIC)and Minimum Description Length(MDL)criterion not only require a huge amount of computation,but also reduce the performance or even cannot correctly work under the condition of low SNR or few snapshots.A novel source number estimation method based on subspace analysis is proposed.Firstly,the subspace estimation of the signal is completed fast by using Multi-stage Wiener Filter(MWF),then the projection value of array signal covariance in subspace matched filters is calculated.At last,the number of sources is obtained by analyzing their orthogonality.The simulation results show that the proposed method has better performance than other algorithms mentioned above in the low SNR or few snapshots,and the amount of calculation is greatly reduced.

关 键 词：阵列信号处理 信源个数估计 子空间估计 多级维纳滤波 空间匹配滤波器 

分 类 号：TN911.72[电子电信—通信与信息系统]