Two-Dimensional Frequencies Estimation Using Two-Stage Separated Virtual Steering Vector-Based Algorithm

In this paper, we develop a novel two-stage separated virtual steering vector- (SVSV-) based algorithm without association operation to estimate 2D frequencies. The key points of this algorithm are (i) in the first stage, this paper rearranges the measurement data as virtual rectangular array data m...

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Published in:	EURASIP journal on advances in signal processing Vol. 2011; no. 1
Main Authors:	Liu, Ding, Liang, Junli
Format:	Journal Article
Language:	English
Published:	Cham Springer International Publishing 01.01.2011 Springer Nature B.V
Subjects:	Algorithms Decomposition Engineering Estimates Maximum entropy method NMR Nuclear magnetic resonance Quantum Information Technology Research Article Science Signal,Image and Speech Processing Spintronics Studies Wireless communications Singular Value Decomposition Frequency Estimation Data Matrix Array Data Full Article
ISSN:	1687-6180, 1687-6172, 1687-6180
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Abstract	In this paper, we develop a novel two-stage separated virtual steering vector- (SVSV-) based algorithm without association operation to estimate 2D frequencies. The key points of this algorithm are (i) in the first stage, this paper rearranges the measurement data as virtual rectangular array data matrix and obtains the propagator from the data matrix using least-squares operator. In addition, the virtual steering vector can be separated into two parts using the introduced electric angle that combines 2D frequencies (to avoid incorrect association especially when multiple 2D frequencies have the same frequency at some dimension), and thus the electric angle and the first part of separated steering vector can be estimated using the derived rank-reduction propagator method; (ii) in the second stage, this paper estimates the second part of separated steering vector using another least-squares operator and obtains 2D frequencies from the recovered steering vector. The resultant SVSV algorithm does not require spectral search or pairing parameters or singular value decomposition (SVD) of data matrix. Simulation results are presented to validate the performance of the proposed method.
AbstractList	In this paper, we develop a novel two-stage separated virtual steering vector- (SVSV-) based algorithm without association operation to estimate 2D frequencies. The key points of this algorithm are (i) in the first stage, this paper rearranges the measurement data as virtual rectangular array data matrix and obtains the propagator from the data matrix using least-squares operator. In addition, the virtual steering vector can be separated into two parts using the introduced electric angle that combines 2D frequencies (to avoid incorrect association especially when multiple 2D frequencies have the same frequency at some dimension), and thus the electric angle and the first part of separated steering vector can be estimated using the derived rank-reduction propagator method; (ii) in the second stage, this paper estimates the second part of separated steering vector using another least-squares operator and obtains 2D frequencies from the recovered steering vector. The resultant SVSV algorithm does not require spectral search or pairing parameters or singular value decomposition (SVD) of data matrix. Simulation results are presented to validate the performance of the proposed method.
ArticleNumber	980349
Author	Liu, Ding Liang, Junli
Author_xml	– sequence: 1 givenname: Ding surname: Liu fullname: Liu, Ding organization: School of Automation & Information Engineering, Xi'an University of Technology – sequence: 2 givenname: Junli surname: Liang fullname: Liang, Junli email: heery_2004@hotmail.com organization: School of Automation & Information Engineering, Xi'an University of Technology
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CitedBy_id	crossref_primary_10_1016_j_sigpro_2012_05_010 crossref_primary_10_1109_TAP_2012_2224832
Cites_doi	10.1109/TSP.2008.917929 10.1109/TSP.2006.877654 10.1109/78.890367 10.1109/TSP.2006.882077 10.1016/j.sigpro.2010.12.001 10.1109/29.17507 10.1109/78.286959 10.1109/TSP.2006.885813 10.1109/29.32276 10.1109/78.157205 10.1109/29.60114 10.1109/78.157226 10.1109/TIM.2010.2086610 10.1109/TAP.2010.2046838
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Copyright	D. Liu and J. Liang. 2011. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Copyright © 2011 Ding Liu and Junli Liang. Ding Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright_xml	– notice: D. Liu and J. Liang. 2011. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. – notice: Copyright © 2011 Ding Liu and Junli Liang. Ding Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Title	Two-Dimensional Frequencies Estimation Using Two-Stage Separated Virtual Steering Vector-Based Algorithm
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