An Improved SVD Algorithm Based on Virtual Matrix

Author

Jun, Kang ; Dengshan, Huang ; Huifu, Cai ; Dajun, Wang

Author_Institution

Sch. of Electron. & Inf., Northwestern Polytech. Univ., Xi´´an, China

Volume

1

fYear

2010

fDate

11-12 May 2010

Firstpage

595

Lastpage

598

Abstract

In this paper, an improved singular value decomposition (SVD) algorithm for high-resolution direction of arrival (DOA) estimation is proposed, which is based on virtual matrix, the SVD-VM algorithm for short. The virtual matrix is employed as the preprocessor for the uniform linear array (ULA), and then the rotational matrix in ESPRIT is used to estimate the directions of the coherent sources. The simulation results show that the SVD-VM algorithm provides higher resolution and robustness performance for coherent signals estimation than conventional singular value decomposition.

Keywords

array signal processing; covariance matrices; direction-of-arrival estimation; program processors; singular value decomposition; ESPRIT; coherent signal estimation; covariance matrix; direction of arrival estimation; improved SVD algorithm; preprocessor; rotation invariance techniques; rotational matrix; singular value decomposition algorithm; uniform linear array; virtual matrix; Covariance matrix; Direction of arrival estimation; Eigenvalues and eigenfunctions; Matrix decomposition; Sensor arrays; Signal processing; Signal processing algorithms; Signal resolution; Singular value decomposition; Smoothing methods; coherent signal; direction of arrival (DOA); low SNR; singular value decomposition (SVD); virtual matrix;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on

Conference_Location

Changsha

Print_ISBN

978-1-4244-7279-6

Electronic_ISBN

978-1-4244-7280-2

Type

conf

DOI

10.1109/ICICTA.2010.359

Filename

5522923