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
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;
Conference_Titel :
Sensor Array and Multichannel Signal Processing Workshop (SAM), 2010 IEEE
Conference_Location :
Jerusalem
Print_ISBN :
978-1-4244-8978-7
Electronic_ISBN :
1551-2282
DOI :
10.1109/SAM.2010.5606744