Multi-dimensional EEF Criterion for Source Number Estimation

被引:0
|
作者
Huang Qinghua [1 ]
Wang Tong [2 ]
机构
[1] Shanghai Univ, Sch Commun & Informat Engn, Shanghai 200072, Peoples R China
[2] Shanghai Second Polytech Univ, Inst Comp & Informat, Shanghai 201209, Peoples R China
基金
中国国家自然科学基金;
关键词
Source enumeration; Exponential embedded family; Multi-dimensional structure; Tensor model; SOURCE ENUMERATION; ORDER; DECOMPOSITION;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
When the number of snapshots is smaller than the dimension of the measured data, Exponential embedded family (EEF) rule fails to choose the correct model order. It is modified in this paper to enumerate sources in three-dimensional space unlimited by the number of snapshots. Then the modified EEF criterion is extended to R-D version for the multi-dimensional data model based on Higher-order singular value decomposition (HOSVD). The R-D EEF criterion exploits the multi-dimensional structure of measurements and the eigenvalues of different mode sample covariance matrices jointly. It improves accuracy and robustness compared with the modified EEF criterion. Simulation results demonstrate the performance of the proposed enumerators.
引用
收藏
页码:503 / 507
页数:5
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