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A fast phase calibration method for a liquid crystal microwave phased array antenna assisted by neural network

Published online by Cambridge University Press:  13 August 2024

Qianying Yan Open the ORCID record for Qianying Yan [Opens in a new window] ,
Yanwei Huang Open the ORCID record for Yanwei Huang [Opens in a new window] ,
Wenzhao Zhang ,
Xin Hou ,
Mengqing Zhang ,
Xiangru Wang  and
Feng Liang
Qianying Yan
Affiliation:
School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China
Yanwei Huang
Affiliation:
School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China
Wenzhao Zhang
Affiliation:
School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China
Xin Hou
Affiliation:
School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China
Mengqing Zhang
Affiliation:
School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China
Xiangru Wang*
Affiliation:
School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China
Feng Liang
Affiliation:
School of Physics, University of Electronic Science and Technology of China, Chengdu, China
*
Corresponding author: Xiangru Wang; Email: [email protected]
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Abstract

Liquid crystal microwave phased arrays (LC-MPAs) are regarded as an ideal approach to realize compact antennas owing to their advantages in cost, size, weight, and power consumption. However, the shortcoming in low radiation deflection efficiency has been one of LC-MPAs’ main application limitations. To optimize the steering performance of LC-MPAs, it is essential to model the channel imperfections and compensate for the phase errors. In this paper, a phase error estimation model is built by training a neural network to establish a nonlinear relationship between the near-field phase error and the far-field pattern, hence realizing fast calibration for LC-MPAs within several measured patterns. Simulations and experiments on a 64-channel, two-dimensional planar antenna were conducted to validate this method. The results show that this method offers precise phase error estimations of 3.58° on average, realizes a fast calibration process with several field-measured radiation patterns, and improves the performances of the LC-MPA by approximately 4%–10% in deflection efficiency at different steering angles.

Keywords

liquid crystalmicrowave phased arrayneural networkphase calibration
Type
Research Paper
Information
International Journal of Microwave and Wireless Technologies , First View , pp. 1 - 10
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Copyright
© The Author(s), 2024. Published by Cambridge University Press in association with The European Microwave Association.

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