Electromagnetic Illusion Device Based on Diffraction Neural Network

ABSTRACT In recent years, electromagnetic illusion technology has used metasurface technology to accurately manipulate radar wavefront, which enhances the controllability and adaptability of electromagnetic engineering. However, traditional metasurface‐based electromagnetic illusion technology faces the problem of difficulty in achieving far‐field measurement conditions, and phase acquisition in near‐field measurement is difficult. Therefore, this paper proposes an electromagnetic camouflage device based on a diffraction neural network (DNN). The device can perform phase‐free near‐field testing to determine the radar cross‐section (RCS) of the target. Using this device, we can use metasurface technology to reconstruct RCS. The mean square error (MSE) between the reconstructed RCS and the target RCS is below 0.02, which has great potential in military applications.

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Publication Details

Journal
Microwave and Optical Technology Letters
Published
2025-03-01
DOI
https://doi.org/10.1002/mop.70167
Primary Topic
Advanced Optical Imaging Technologies
Type
article
Field-Weighted Citation Impact
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article

Electromagnetic Illusion Device Based on Diffraction Neural Network

X. H. Liu, Lijie Chen, Gengjiang Yao, Li Deng
Microwave and Optical Technology Letters
Advanced Optical Imaging Technologies
article

Electromagnetic Illusion Device Based on Diffraction Neural Network

X. H. Liu, Lijie Chen, Gengjiang Yao, Li Deng
article en

Abstract

ABSTRACT In recent years, electromagnetic illusion technology has used metasurface technology to accurately manipulate radar wavefront, which enhances the controllability and adaptability of electromagnetic engineering. However, traditional metasurface‐based electromagnetic illusion technology faces the problem of difficulty in achieving far‐field measurement conditions, and phase acquisition in near‐field measurement is difficult. Therefore, this paper proposes an electromagnetic camouflage device based on a diffraction neural network (DNN). The device can perform phase‐free near‐field testing to determine the radar cross‐section (RCS) of the target. Using this device, we can use metasurface technology to reconstruct RCS. The mean square error (MSE) between the reconstructed RCS and the target RCS is below 0.02, which has great potential in military applications.

Microwave and Optical Technology LettersVol. 67(3)
Beijing University of Posts and Telecommunications (CN), Wuhan Ship Development & Design Institute (CN), Huazhong University of Science and Technology (CN)
Openalex Percentile: Top 93%
Advanced Optical Imaging Technologies
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