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Sensors 2017, 17(5), 963; doi:10.3390/s17050963

A Type-2 Block-Component-Decomposition Based 2D AOA Estimation Algorithm for an Electromagnetic Vector Sensor Array

1
School of Electronic Engineering, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave., West Hi-Tech Zone, Chengdu 611731, China
2
College of Telecommunication and Information Engineering, Nanjing University of Posts and Telecommunications, 66 Xinmofan Road, Nanjing 210003, China
*
Author to whom correspondence should be addressed.
Academic Editor: Zhiguo Shi
Received: 18 January 2017 / Revised: 17 April 2017 / Accepted: 18 April 2017 / Published: 27 April 2017
View Full-Text   |   Download PDF [1434 KB, uploaded 27 April 2017]   |  

Abstract

This paper investigates a two-dimensional angle of arrival (2D AOA) estimation algorithm for the electromagnetic vector sensor (EMVS) array based on Type-2 block component decomposition (BCD) tensor modeling. Such a tensor decomposition method can take full advantage of the multidimensional structural information of electromagnetic signals to accomplish blind estimation for array parameters with higher resolution. However, existing tensor decomposition methods encounter many restrictions in applications of the EMVS array, such as the strict requirement for uniqueness conditions of decomposition, the inability to handle partially-polarized signals, etc. To solve these problems, this paper investigates tensor modeling for partially-polarized signals of an L-shaped EMVS array. The 2D AOA estimation algorithm based on rank- ( L 1 , L 2 , · ) BCD is developed, and the uniqueness condition of decomposition is analyzed. By means of the estimated steering matrix, the proposed algorithm can automatically achieve angle pair-matching. Numerical experiments demonstrate that the present algorithm has the advantages of both accuracy and robustness of parameter estimation. Even under the conditions of lower SNR, small angular separation and limited snapshots, the proposed algorithm still possesses better performance than subspace methods and the canonical polyadic decomposition (CPD) method. View Full-Text
Keywords: EMVS; L-shaped array; partial polarization; 2D AOA; rank-(L1, L2,·) BCD; tensor decomposition EMVS; L-shaped array; partial polarization; 2D AOA; rank-(L1, L2,·) BCD; tensor decomposition
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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. (CC BY 4.0).

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Gao, Y.-F.; Gui, G.; Xie, W.; Zou, Y.-B.; Yang, Y.; Wan, Q. A Type-2 Block-Component-Decomposition Based 2D AOA Estimation Algorithm for an Electromagnetic Vector Sensor Array. Sensors 2017, 17, 963.

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