DocumentCode
2631029
Title
Expected likelihood support for deterministic maximum likelihood DOA estimation
Author
Abramovich, Yuri I. ; Johnson, Ben A.
Author_Institution
Intell., Surveillance & Reconnaissance Div., Defence Sci. & Technol. Organ., Edinburgh, SA, Australia
fYear
2010
fDate
4-7 Oct. 2010
Firstpage
237
Lastpage
240
Abstract
In this paper, the “expected likelihood” approach, previously introduced for the stochastic (unconditional) Gaussian case, is extended over the so-called deterministic (conditional) Gaussian case. Direction of arrival (DOA) estimation when arbitrary temporally correlated waveforms transmitted by point sources of interest impinge onto a uniformly spaced linear array is examined. Specifically, we introduce a normalized likelihood ratio that for the true DOAs have p.d.fs that (for practical purposes) have weak enough dependence on these DOAs to be used in the expected likelihood approach. The utility of this approach is demonstrated by examples on DOA estimation in the so-called “threshold” region.
Keywords
Gaussian processes; direction-of-arrival estimation; maximum likelihood estimation; stochastic processes; DOA; direction of arrival; maximum likelihood estimation; normalized likelihood ratio; spaced linear array; stochastic Gaussian; Arrays; Direction of arrival estimation; Eigenvalues and eigenfunctions; Maximum likelihood estimation; Multiple signal classification; Signal to noise ratio;
fLanguage
English
Publisher
ieee
Conference_Titel
Sensor Array and Multichannel Signal Processing Workshop (SAM), 2010 IEEE
Conference_Location
Jerusalem
ISSN
1551-2282
Print_ISBN
978-1-4244-8978-7
Electronic_ISBN
1551-2282
Type
conf
DOI
10.1109/SAM.2010.5606744
Filename
5606744
Link To Document