DocumentCode :
1651195
Title :
A Bayesian approach for jointly estimating the model order and the DOAs
Author :
Mei-na, Jin ; Yong-jun, Zhao ; Jiang-wei, Ge
Author_Institution :
Zhengzhou Inf. Sci. & Technol. Inst., Zhengzhou
fYear :
2008
Firstpage :
345
Lastpage :
348
Abstract :
In this paper, a new array signal model structure based on signal reconstruction is proposed, that allows us to define a posterior distribution on the parameter space, which is applicable to both wideband and narrowband signal. The proposed method lends itself well to a Bayesian approach for jointly estimating the model order and the DOAs. We develop a hybrid MCMC algorithm based on reversible jump Markov chain Monte Carlo method to perform the Bayesian computation. Computer simulation results show that the correctness and efficiency of the new method, and significantly fewer observations and only real arithmetic is required.
Keywords :
Bayes methods; Markov processes; Monte Carlo methods; array signal processing; direction-of-arrival estimation; signal reconstruction; Array signal processing; Bayesian approach; DOA estimation; Markov chain; Monte Carlo method; direction-of-arrival estimation; hybrid MCMC algorithm; model order estimation; signal reconstruction; Acoustic signal processing; Array signal processing; Bayesian methods; Biomedical signal processing; Direction of arrival estimation; Radar signal processing; Sampling methods; Sensor arrays; Signal processing algorithms; Signal reconstruction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing, 2008. ICSP 2008. 9th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-2178-7
Electronic_ISBN :
978-1-4244-2179-4
Type :
conf
DOI :
10.1109/ICOSP.2008.4697141
Filename :
4697141
Link To Document :
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