Open AccessReduced-Dimension DOA and Polarization Parameters Joint Estimation Method for Electromagnetic Vector Sensor Array
Author(s) -
Xiouhua Fu,
Tao Wan,
Shixin Wang
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1325/1/012217
Subject(s) - algorithm , computational complexity theory , direction of arrival , polarization (electrochemistry) , computer science , curse of dimensionality , estimation theory , dimensionality reduction , mathematics , artificial intelligence , telecommunications , chemistry , antenna (radio)
MUSIC algorithm is a very typical algorithm in the joint estimation of DOA and polarization parameters. But the two spectral peak searches of two-dimensional parameter space in the algorithm cause a damaging effect on calculation, which limits the application of the algorithm in practice. Therefore, this paper proposes a joint estimation algorithm of dimensionality reduction DOA and polarization parameters based on successive MUSIC in the case of uniform linear array arrangement of the electromagnetic vector sensor. The proposed algorithm improves the classical MUSIC algorithm from two two-dimensional parameter searches to four one-dimensional parameter searches in the joint estimation of DOA and polarization parameters, which greatly reduces the computational complexity of the algorithm and can lead to the automatic matching of DOA and polarization parameters. Simulation results show that the computational complexity of the proposed algorithm is reduced by 10 4 orders of magnitude compared to the classical MUSIC algorithm. And the performance of the polarization parameter estimation of this algorithm is about 72%∼85% higher than that of the ESPRIT algorithm. Therefore, the algorithm is more applicable.