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Maximum-likelihood DOA estimation by data-supported grid search

delete1999-10-01
delete123
PRE
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P
Petre Stoica *
A
A.B. Gershman
DOI：10.1109/97.789608delete
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Abstract

Abstract

En 中文
After reviewing the main existing methods for determining the maximum-likelihood (ML) estimates of the direction-of-arrival (DOA) parameters in array signal processing applications, we introduce a new conceptually simple and computationally effective approach that consists of maximizing the likelihood function (LF) over a set of points derived from the data. We show that the data-supported grid search of the LF provides a performance similar to that achieved by a genetic algorithm (GA), but at a significantly lower computational cost. We use an ESPRIT-like algorithm to obtain the grid points with support in the data, although our approach is not limited to this choice.
Keywords:
array processing
data-supported optimization
maximum likelihood
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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

IEEE Signal Processing Magazine cover
IEEE Signal Processing Magazine
IF:
9.6
Papers:
1.1W
Citations:
1.7W

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No organization information available