Parametric direction of arrival estimation in the small sample-size case

The problem of direction of arrival estimation in array processing is considered in this paper. The focus is on how to estimate the source parameters accurately in the absence of a large number of snapshots. A parametric iterative adaptive algorithm based on amplitude and phase estimation with low c...

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Bibliographic Details
Published in2010 International Conference on Image Analysis and Signal Processing pp. 523 - 527
Main Authors Manlin Xiao, Xin Qi, Ping Wei
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.04.2010
Subjects
Adaptive algorithm
Array signal processing
Computational complexity
Delay estimation
Direction of arrival estimation
DOA estimation
Iterative algorithms
parametric iterative adaptive algorithm
Phase estimation
Sensor arrays
Signal processing algorithms
Signal resolution
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Summary:The problem of direction of arrival estimation in array processing is considered in this paper. The focus is on how to estimate the source parameters accurately in the absence of a large number of snapshots. A parametric iterative adaptive algorithm based on amplitude and phase estimation with low computational complexities is proposed in this paper. Eigen-decomposition and the subspace projection are avoided in the proposed algorithm, such that the negative influence of subspace swap phenomena is weakened. This estimator is suitable for DOA estimation in the finite sample-size scenario, especially for resolving closely spaced sources. Numerical evaluations indicate that the estimator has a better performance than the MUSIC algorithm in the small sample-size scenario, where the observation dimension and the sample size are comparable in magnitude.
ISBN:1424455545
9781424455546
ISSN:2156-0110
DOI:10.1109/IASP.2010.5476063