Direction-of-arrival estimation based on modified Bayesian compressive sensing method

Author

Lei, Sun ; Huali, Wang

Author_Institution

Postgrad. Team 2, PLAUST, Nanjing, China

fYear

2011

fDate

9-11 Nov. 2011

Firstpage

1

Lastpage

4

Abstract

In this paper, the narrowband DOA estimation problem is studied in compressive sensing (CS) perspective. A novel DOA estimation approach based on extended Bayesian compressive sensing (BCS) is presented. To avoid the matrix singular drawback in BCS, a basis pruning procedure through iterative hard thresholding is utilized. The proposed method is hyper-parameter free and needs not know the number of sources a prior. Simulation results demonstrate that the proposed scheme has high space resolution and can resolve highly correlated or coherent sources.

Keywords

Bayes methods; compressed sensing; direction-of-arrival estimation; iterative methods; coherent source; correlated source; direction-of-arrival estimation; high space resolution; hyperparameter free; iterative hard thresholding; matrix singular drawback; modified Bayesian compressive sensing method; narrowband DOA estimation problem; pruning procedure; Arrays; Bayesian methods; Compressed sensing; Direction of arrival estimation; Estimation; Sensors; Vectors; Bayesian compressive sensing; basis pruning; direction-of-arrival (DOA); iterative hard thresholding;

fLanguage

English

Publisher

ieee

Conference_Titel

Wireless Communications and Signal Processing (WCSP), 2011 International Conference on

Conference_Location

Nanjing

Print_ISBN

978-1-4577-1009-4

Electronic_ISBN

978-1-4577-1008-7

Type

conf

DOI

10.1109/WCSP.2011.6096869

Filename

6096869