Title :
Unconditional maximum likelihood approach for near-field source localization
Author :
Cekli, Erdinc ; Cirpan, Hakan A.
Author_Institution :
Dept. of Electr. Eng., Istanbul Univ., Turkey
fDate :
6/23/1905 12:00:00 AM
Abstract :
Localization of near-field sources requires sophisticated estimation algorithms. In this paper, we propose an unconditional maximum likelihood method for estimating direction of arrival and angle parameters of near-field sources. However, calculation of ML estimation from the corresponding likelihood function results in a difficult nonlinear constraint optimization problem. We therefore employed an expectation/maximization iterative method to obtain ML estimates. The most important feature of the EM algorithm is that it decomposes the observed data into its components and then estimates the parameters of each signal component separately providing a computationally efficient solution to the resulting optimization problem
Keywords :
array signal processing; direction-of-arrival estimation; iterative methods; maximum likelihood estimation; optimisation; parameter estimation; EM algorithm; ML estimates; ML estimation; angle parameters estimation; computationally efficient solution; data decomposition; direction of arrival parameters estimation; estimation algorithms; expectation/maximization iterative method; near-field source localization; near-field sources; nonlinear constraint optimization; optimization problem; signal component parameters; unconditional maximum likelihood approach; unconditional maximum likelihood method; Additive noise; Azimuth; Constraint optimization; Direction of arrival estimation; Iterative algorithms; Iterative methods; Maximum likelihood estimation; Narrowband; Parameter estimation; Sensor arrays;
Conference_Titel :
Electronics, Circuits and Systems, 2001. ICECS 2001. The 8th IEEE International Conference on
Print_ISBN :
0-7803-7057-0
DOI :
10.1109/ICECS.2001.957584