Presentation 2005/6/9
Efficient Iterative Algorithms for Maximum Likelihood Bearing Estimation
Tingting TENG, Ming ZHANG, Wei FAN, Masakiyo SUZUKI,
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Abstract(in English) This paper presents an improvement of the Alternating Projection (AP) algorithm for the Maximum Likelihood bearing estimation using a uniform linear array of sensors. Solutions by the AP algorithm may oscillate because of numerical instability which occurs due to indefiniteness of the AP criterion, when bearings more than one approach to the identical value. The oscillation makes the condition for terminating iterations complex. This paper derives a irreduccible form of the AP criterion, which never get indefinite, to overcome this defect. The irreducible form has the advantage of not only suppressing the oscillation but also being efficient since the order of the amount of arithmetic operations in each step of iteration decreases. Furthermore FFT and gradient methods, such as the Newton method, can be applied to recuce the operations.
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Keyword(in English) DOA finding / maximum likelihood estismation / fast algorithm / FFT / Newton method
Paper # SIS2005-5
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Conference Date 2005/6/9(1days)
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Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Efficient Iterative Algorithms for Maximum Likelihood Bearing Estimation
Sub Title (in English)
Keyword(1) DOA finding
Keyword(2) maximum likelihood estismation
Keyword(3) fast algorithm
Keyword(4) FFT
Keyword(5) Newton method
1st Author's Name Tingting TENG
1st Author's Affiliation Graduate School of Computer Science, Kitami Institute of Technology()
2nd Author's Name Ming ZHANG
2nd Author's Affiliation Graduate School of Computer Science, Kitami Institute of Technology
3rd Author's Name Wei FAN
3rd Author's Affiliation Graduate School of Computer Science, Kitami Institute of Technology
4th Author's Name Masakiyo SUZUKI
4th Author's Affiliation Department of Computer Science, Kitami Institute of Technology
Date 2005/6/9
Paper # SIS2005-5
Volume (vol) vol.105
Number (no) 111
Page pp.pp.-
#Pages 6
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