Title :
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
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;
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
DOI :
10.1109/ICICTA.2010.359
