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Maximum Likelihood
Approach to Joint Array Detection/Estimation
2004 Award Winner
Roy E. Bethel, The MITRE Corporation
Kristine L. Bell, George Mason University
ABSTRACT
The problem of detecting the number of (possibly correlated)
narrowband sources of energy and estimating the direction
of arrival (DOA) of each detected source using data received
by an array of sensors is investigated. A combined detection
and estimation approach based on the likelihood function
(LF) is used. The approach is motivated by detection theoretic
considerations instead of information theoretic criteria and
uses maximum likelihood (ML) signal-to-noise ratio (SNR)
estimates of hypothesized sources as detection statistics rather
than maximizing the LF with a penalty function. Performance
comparisons are made to unstructured and structured techniques
based on Akaike information theoretic criteria (AIC), minimum
description length (MDL), and Bayesian predictive density (BPD)
approaches as well as the Minimum Variance Distortionless
Response (MVDR) approach. An important feature that
distinguishes this approach is the ability to trade off detection
and false alarm performance, which is not possible with the
other LF-based approaches, while achieving performance levels
comparable to or exceeding the LF-based and MVDR approaches.
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Publication
Copyright ©2004 IEEE. Reprinted from IEEE Transactions on Aerospace and Electronic Systems, Vol. 40, No. 3, pp. 1060–1072. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of MITRE Corporation's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
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