Joint estimation for DOA and polarization parameters of  orthogonal dipole array based on compressive sensing

WANG Weitong; YANG Jian; GUO Xiaoran; LIU Lutao

doi:10.19693/j.issn.1673-3185.02262

Volume 17 Issue 1

Mar. 2022

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Chinese Journal of Ship Research > 2022 > 17(1): 221-226. > DOI: 10.19693/j.issn.1673-3185.02262 CSTR: 32390.14.j.issn.1673-3185.02262

WANG W T, YANG J, GUO X R, et al. Joint estimation for DOA and polarization parameters of orthogonal dipole array based on compressive sensing[J]. Chinese Journal of Ship Research, 2022, 17(1): 221–226, 234. DOI: 10.19693/j.issn.1673-3185.02262

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Joint estimation for DOA and polarization parameters of orthogonal dipole array based on compressive sensing

WANG Weitong^{1, 2, ,},
YANG Jian^{1, 2, 3,},
GUO Xiaoran⁴,
LIU Lutao^{1, 2,}

1.
College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China
2.
MIIT Key Laboratory of Advanced Marine Communication and Information Technology, Harbin 150001, China
3.
Beijing Institute of Remote Sensing Equipment, Beijing 100854, China
4.
The 32181 Unit of PLA, Shijiazhuang 050000, China

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Received Date: January 07, 2021
Revised Date: April 06, 2021
Available Online: November 18, 2021

This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Abstract

Objectives As the detection-of-arrival (DOA) estimation algorithm used in traditional polarization sensitive arrays has such problems as high computation complexity and poor real-time performance, this study proposes a data compression-based orthogonal dipole polarization sensitive array structure.
Methods By applying compression sensing technology to the system design (i.e., data compression technology), the proposed structure compresses the dimensions of the receiving signal vector, controls the complexity of the system by reducing the number of front-end chains, and brings high flexibility to the array structure design. At the same time, a dimensionality reduction-based multiple signal classification (MUSIC) algorithm is also proposed. First, the DOA estimation of signals is realized through spatial spectrum searching. The Lagrange multiplier method is then used to reduce the searching dimensionality, and the signal polarization parameters are obtained by solving the optimization problem.
Results Simulation experiments show that the proposed array structure and MUSIC algorithm can correctly estimate DOA and polarization parameters when the incident signals are completely polarized and incoherent. When the signal-noise ratio (SNR) is greater than 10 dB, the root mean square error (RMSE) of the elevation angle is less than 0.05°.
Conclusions Compared with the non-compressed structure with an equal channel number under the same conditions, the proposed structure can provide higher estimation accuracy and lower computational complexity.

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Joint estimation for DOA and polarization parameters of orthogonal dipole array based on compressive sensing

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