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Multi-Bit Phase-Coded Metamaterial With Honeycomb EM Structure for Scattering Manipulation Using Deep Learning-Based Method

delete2025-06-01
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PRE
AI
W
Weizhi Chen
L
Liu, Jiawei
X
Xin Xiu *
唐锟 cover
唐锟 (Kun Tang)
W
Wenjie Feng
W
Wenquan Che *
DOI:10.1109/TMTT.2025.3574674delete
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Abstract

Abstract

En 中文
A deep-learning inverse design method for generating multi-bit phase-coded metamaterials is proposed, aiming at broadband electromagnetic (EM) scattering manipulation with stable performance under oblique incidence. First, a deep learning-based approach for broadband phase gradient manipulation is analyzed using an equivalent circuit model (ECM), resulting in a bandwidth of 8.0-18.0 GHz. Then, to enhance performance under oblique incidence, a miniaturized folded tightly coupled dipole structure is proposed to suppress parasitic resonance. Furthermore, a design method combining deep learning with intelligent optimization algorithms is investigated to generate and optimize the dipole, ensuring stable operation at incident angles up to 45 degrees. By leveraging ECM principles and previous EM knowledge, the physical dimensions of the unit cell generated by the deep-learning model are reduced from five to four parameters, and five-bit phase-coded unit cells are generated accordingly. Finally, a novel phase-coded metamaterial based on a honeycomb EM structure consisting of 29x33 unit cells, with a thickness of 0.36 lambda(C) and a periodicity of 10.3 mm, is designed and simulated for radar cross-section (RCS) reduction under linear polarization (LP) incident waves. For demonstration, one prototype is fabricated and measured. The results indicate a broadband phase gradient from 8.0 to 18.0 GHz (76.9%) up to an incident angle of 45 degrees in the case of dual LP. Regarding RCS reduction, the scattering far-field is reduced by more than 20 dBsm under LP normal incidence, with a 10 dBsm reduction maintained even at a 45 degrees oblique incidence.
Keywords:
Metamaterials
Broadband communication
Resonance
Metasurfaces
Electric fields
Design methodology
Radar cross-sections
Permittivity
Permeability
Millimeter wave radar
Deep learning
generative model
honeycomb electromagnetic (EM) structure
phase manipulation
phase-coded metamaterial
radar cross-section (RCS) reduction

Journal

IEEE Transactions on Microwave Theory and Techniques cover
IEEE Transactions on Microwave Theory and Techniques
IF:
4.5
Papers:
593
Citations:
3.5W

Organization

S
south china normal university
Scholars:
2.0W
Papers: 1.3W
Citations: 13
S
south china university of technology
Scholars:
6.7W
Papers: 5.1W
Citations: 85