NDLI: An Importance Sampling Maximum Likelihood Direction of Arrival Estimator

Content Provider	IEEE Xplore Digital Library
Author	Huigang Wang Kay, S. Saha, S.
Copyright Year	1991
Abstract	We present a new implementation for maximum likelihood (ML) estimation of the direction of arrival (DOA) of multiple narrow-band plane waves in noise. The proposed estimator can be applied to the estimation of DOAs of both deterministic and stochastic signals. In this paper, we discuss the estimation of DOAs for stochastic signals only. The proposed method uses a global optimization procedure to maximize the compressed likelihood function, which is a function of only the DOAs. The procedure is based on Monte Carlo importance sampling. It is shown via simulations that the method allows for estimation of DOAs at low angular separation and in situations for which other suboptimal techniques may fail. The improved performance of this method is due to its guaranteed convergence to a global maximum, which is not true for the iterative ML methods, as, for example, the WSF, MODE(X), and EM algorithms. We compare our method to the latter algorithms to show that the proposed method outperforms the iterative approaches for closely spaced narrow-band sources.
Sponsorship	IEEE Signal Processing Society
Starting Page	5082
Ending Page	5092
Page Count	11
File Size	983813
File Format	PDF
ISSN	1053587X
Volume Number	56
Issue Number	10
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Monte Carlo methods Maximum likelihood estimation Direction of arrival estimation Iterative methods Stochastic processes Narrowband Sensor arrays Stochastic resonance Iterative algorithms Amplitude estimation signal resolution Estimation signal analysis
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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