Low-complexity ESPRIT method for direction finding

A low-complexity ESPRIT method for direction-of-arrival (DOA) estimation is proposed in this paper. Unlike the conventional subspace based methods for DOA estimation, the proposed method only needs the training data of one signal to perform the forward recursions of the multi-stage Wiener filter (MS...

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Published inProceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005 Vol. 4; pp. iv/929 - iv/932 Vol. 4
Main Authors Lei Huang, Shunjun Wu, Linrang Zhang
Format Conference Proceeding
LanguageEnglish
Published IEEE 2005
Subjects
Background noise
Computational complexity
Covariance matrix
Direction of arrival estimation
Geophysics computing
Multiple signal classification
Recursive estimation
Rockets
Sensor arrays
Wiener filter
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Summary:A low-complexity ESPRIT method for direction-of-arrival (DOA) estimation is proposed in this paper. Unlike the conventional subspace based methods for DOA estimation, the proposed method only needs the training data of one signal to perform the forward recursions of the multi-stage Wiener filter (MSWF), does not involve the estimate of the covariance matrix or its eigendecomposition. Thus, the proposed method is computationally advantageous. Numerical results are given to illustrate the performance of the proposed method.
ISBN:9780780388741
0780388747
ISSN:1520-6149
2379-190X
DOI:10.1109/ICASSP.2005.1416162