Sparse Planar Array Synthesis Using Matrix Enhancement and Matrix Pencil

The matrix enhancement and matrix pencil (MEMP) plays important roles in modern signal processing applications. In this paper, MEMP is applied to attack the problem of two-dimensional sparse array synthesis. Firstly, the desired array radiation pattern, as the original pattern for approximating, is...

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Vydáno v:International journal of antennas and propagation Ročník 2013; číslo 2013; s. 1 - 7
Hlavní autoři: Liu, Xian-pan, Wu, Hong-gang, Chen, Ke-song, Zheng, Mei-yan
Médium: Journal Article
Jazyk:angličtina
Vydáno: Cairo, Egypt Hindawi Puplishing Corporation 01.01.2013
Hindawi Publishing Corporation
Wiley
ISSN:1687-5869, 1687-5877
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Abstract The matrix enhancement and matrix pencil (MEMP) plays important roles in modern signal processing applications. In this paper, MEMP is applied to attack the problem of two-dimensional sparse array synthesis. Firstly, the desired array radiation pattern, as the original pattern for approximating, is sampled to form an enhanced matrix. After performing the singular value decomposition (SVD) and discarding the insignificant singular values according to the prior approximate error, the minimum number of elements can be obtained. Secondly, in order to obtain the eigenvalues, the generalized eigen-decomposition is employed on the approximate matrix, which is the optimal low-rank approximation of the enhanced matrix corresponding to sparse planar array, and then the ESPRIT algorithm is utilized to pair the eigenvalues related to each dimension of the planar array. Finally, element positions and excitations of the sparse planar array are calculated according to the correct pairing of eigenvalues. Simulation results are presented to illustrate the effectiveness of the proposed approach.
AbstractList The matrix enhancement and matrix pencil (MEMP) plays important roles in modern signal processing applications. In this paper, MEMP is applied to attack the problem of two-dimensional sparse array synthesis. Firstly, the desired array radiation pattern, as the original pattern for approximating, is sampled to form an enhanced matrix. After performing the singular value decomposition (SVD) and discarding the insignificant singular values according to the prior approximate error, the minimum number of elements can be obtained. Secondly, in order to obtain the eigenvalues, the generalized eigen-decomposition is employed on the approximate matrix, which is the optimal low-rank approximation of the enhanced matrix corresponding to sparse planar array, and then the ESPRIT algorithm is utilized to pair the eigenvalues related to each dimension of the planar array. Finally, element positions and excitations of the sparse planar array are calculated according to the correct pairing of eigenvalues. Simulation results are presented to illustrate the effectiveness of the proposed approach.
Author Chen, Ke-song
Zheng, Mei-yan
Liu, Xian-pan
Wu, Hong-gang
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Cites_doi 10.1109/29.56027
10.1109/TAP.2008.928801
10.1109/78.157226
10.1109/PROC.1971.8523
10.1109/TAP.2007.893375
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Contributor Chen, Ke-song
Zheng, Mei-yan
Liu, Xian-pan
Wu, Hong-gang
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Copyright Copyright © 2013 Mei-yan Zheng et al.
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