Title :
Direction-of-arrival estimation based on modified Bayesian compressive sensing method
Author :
Lei, Sun ; Huali, Wang
Author_Institution :
Postgrad. Team 2, PLAUST, Nanjing, China
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;
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
DOI :
10.1109/WCSP.2011.6096869