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Improved Singular Value Decomposition (TopSVD) for Source Number Estimation of Low SNR in Blind Source Separation

Authors :
Hongchun Sun
Jingzheng Guo
Liang Fang
Source :
IEEE Access, Vol 5, Pp 26460-26465 (2017)
Publication Year :
2017
Publisher :
IEEE, 2017.

Abstract

An improved singular value decomposition based on Toeplitz (TopSVD) is proposed to solve the problem of inaccurately estimating source numbers under the condition of a low signal-to-noise (SNR) ratio for blind source separation. First, Toeplitz modifies the covariance of the received data, and singular value decomposition is used to estimate the number of signal sources. The advantages of TopSVD over traditional approaches are demonstrated by simulated signals. The results demonstrate that the proposed method can be used to estimate the number of coherent sources under low SNR conditions; at the same time, it can significantly improve the accuracy of source number estimation under the conditions of a low SNR and coherent signal source with the simple algorithm.

Details

Language :
English
ISSN :
21693536
Volume :
5
Database :
Directory of Open Access Journals
Journal :
IEEE Access
Publication Type :
Academic Journal
Accession number :
edsdoj.b845ccb9e7844638b5dae1952398c59
Document Type :
article
Full Text :
https://doi.org/10.1109/ACCESS.2017.2754487