DocumentCode
2334706
Title
SPC10-4: EM Algorithm for Multiple Wideband Source Localization
Author
Mada, Kiran K. ; Wu, Hsiao-Chun
Author_Institution
Dept. of Electr. & Comput. Eng., Commun. & Signal Processing Lab., Louisiana State Univ., Baton Rouge, LA
fYear
2006
fDate
Nov. 27 2006-Dec. 1 2006
Firstpage
1
Lastpage
5
Abstract
A computationally efficient algorithm for multiple source localization, using the expectation-maximization (EM) algorithm, for the wideband sources in the near field of a sensor array/area, is presented. The basic idea is to decompose the observed sensor data, which is a superimposition of multiple sources, into individual components in the frequency domain and then estimate the corresponding location parameters associated with each component separately. Instead of the conventional alternating projection method, we propose to adopt the EM algorithm in this paper; our method involves two steps, namely Expectation (E-step) and Maximization (M-step). In the E-step, the individual incident source waveforms are estimated. Then, in the M-step, the maximum likelihood estimates of the source location parameters are obtained. These two steps are executed iteratively and alternatively until the pre-defined convergence is reached. The computational complexity comparison between our proposed EM algorithm and the existing alternating projection scheme is investigated. It is shown through Monte Carlo simulations that the computational complexity of the proposed EM algorithm is significantly lower than that of the conventional alternating projection algorithm.
Keywords
Monte Carlo methods; array signal processing; computational complexity; direction-of-arrival estimation; expectation-maximisation algorithm; EM Algorithm; Monte Carlo simulations; computational complexity; direction-of-arrival estimation; expectation-maximization algorithm; individual incident source waveforms; maximum likelihood estimation; multiple wideband source localization; sensor array; sensor data; signal processing; Computational complexity; Convergence; Frequency domain analysis; Frequency estimation; Iterative algorithms; Maximum likelihood estimation; Position measurement; Projection algorithms; Sensor arrays; Wideband;
fLanguage
English
Publisher
ieee
Conference_Titel
Global Telecommunications Conference, 2006. GLOBECOM '06. IEEE
Conference_Location
San Francisco, CA
ISSN
1930-529X
Print_ISBN
1-4244-0356-1
Electronic_ISBN
1930-529X
Type
conf
DOI
10.1109/GLOCOM.2006.589
Filename
4151219
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