DocumentCode :
1928883
Title :
Particle filter based DOA estimation for multiple source tracking (MUST)
Author :
Wiese, Thomas ; Claussen, Heiko ; Rosca, Justinian
Author_Institution :
Sch. of Electr. Eng., Tech. Univ. Munich, Munich, Germany
fYear :
2011
fDate :
6-9 Nov. 2011
Firstpage :
624
Lastpage :
628
Abstract :
Direction of arrival estimation is a well researched topic and represents an important building block for higher level interpretation of data. The Bayesian algorithm proposed in this paper (MUST) can estimate and track the direction of multiple, possibly correlated, wideband sources. MUST approximates the posterior probability density function of the source directions in time-frequency domain with a particle filter. In contrast to other previous algorithms, no time-averaging is necessary, therefore moving sources can be tracked. MUST uses a new low complexity weighting and regularization scheme to fuse information from different frequencies and to overcome the problem of overfitting when few sensors are available.
Keywords :
Bayes methods; direction-of-arrival estimation; particle filtering (numerical methods); Bayesian algorithm; MUST; direction-of-arrival estimation; multiple source tracking; particle filter based DOA estimation; posterior probability density function; regularization scheme; time-frequency domain; Arrays; Bayesian methods; Direction of arrival estimation; Estimation; Noise; Sensors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signals, Systems and Computers (ASILOMAR), 2011 Conference Record of the Forty Fifth Asilomar Conference on
Conference_Location :
Pacific Grove, CA
ISSN :
1058-6393
Print_ISBN :
978-1-4673-0321-7
Type :
conf
DOI :
10.1109/ACSSC.2011.6190077
Filename :
6190077
Link To Document :
بازگشت