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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/40567

Title: ADAPTIVE EIGENDECOMPOSITION ALGORITHMS FOR EIGENSTRUCTURE-BASED ARRAY SIGNAL PROCESSING
Authors: Lena Chang
Contributors: 國立臺灣海洋大學:通訊與導航工程學系
Keywords: eigendecomposition
eigenstructure
Date: 2012
Issue Date: 2017-01-20T05:53:57Z
Publisher: Journal of the Chinese Institute of Engineers
Abstract: Absract: This paper first presents a forward-only algorithm for adaptive eigendecomposition of a continuously updated sample correlation matrix for arbitrary geometry arrays. The proposed forward-only adaptive eigendecomposition (FOAE) algorithm is based on an alternate iteration technique which can alleviate the computation complexity of the standard eigendecomposition. For an MxM matrix, the FOAE algorithm requires O(Mq) complex operations per iteration to adjust the eigencomponents of the signal subspace, where q is the signal subspace dimension. Then, for a symmetrically distributed antenna array, we exploit the Hermitian persymmetric property of the correlation matrix to develop a real-valued forward-backward adaptive eigendecomposition (RFBAE) algorithm. The proposed RFBAE algorithm requires only O(Mq) real operations in each iteration. Moreover, the FOAE and RFBAE algorithms are applied to estimate or track the angles of arrival and design the eigenspace-based beamformer. Simulation results confirm the fast convergence rate of the proposed algorithms and the RFBAE algorithm performs better than the FOAE algorithm.
Relation: 20(4)
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/40567
Appears in Collections:[通訊與導航工程學系] 期刊論文

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