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Sensors 2012, 12(3), 3394-3417; https://doi.org/10.3390/s120303394

Simultaneous Source Localization and Polarization Estimation via Non-Orthogonal Joint Diagonalization with Vector-Sensors

1
School of Information and Communication Engineering, Dalian University of Technology, No. 2 Linggong Road, Dalian 116024, China
2
School of Information and Electronics, Beijing Institute of Technology, 5 South Zhongguancun Street, Beijing 100081, China
*
Author to whom correspondence should be addressed.
Received: 16 January 2012 / Revised: 8 February 2012 / Accepted: 21 February 2012 / Published: 8 March 2012
(This article belongs to the Section Physical Sensors)
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Abstract

Joint estimation of direction-of-arrival (DOA) and polarization with electromagnetic vector-sensors (EMVS) is considered in the framework of complex-valued non-orthogonal joint diagonalization (CNJD). Two new CNJD algorithms are presented, which propose to tackle the high dimensional optimization problem in CNJD via a sequence of simple sub-optimization problems, by using LU or LQ decompositions of the target matrices as well as the Jacobi-type scheme. Furthermore, based on the above CNJD algorithms we present a novel strategy to exploit the multi-dimensional structure present in the second-order statistics of EMVS outputs for simultaneous DOA and polarization estimation. Simulations are provided to compare the proposed strategy with existing tensorial or joint diagonalization based methods. View Full-Text
Keywords: complex non-orthogonal joint diagonalization; direction-of-arrival; polarization; electromagnetic vector-sensor; LU; LQ complex non-orthogonal joint diagonalization; direction-of-arrival; polarization; electromagnetic vector-sensor; LU; LQ
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).
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Gong, X.-F.; Wang, K.; Lin, Q.-H.; Liu, Z.-W.; Xu, Y.-G. Simultaneous Source Localization and Polarization Estimation via Non-Orthogonal Joint Diagonalization with Vector-Sensors. Sensors 2012, 12, 3394-3417.

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