An Electromagnetic Imaging Algorithm Based on Generative Adversarial Network for Limited Observation Angle

作者

  • Chun Xia Yang Shanghai Engineering Research Center of Intelligent Education and Bigdata Shanghai Normal University, Shanghai 200234, China
  • Xirui Yang Shanghai Engineering Research Center of Intelligent Education and Bigdata Shanghai Normal University, Shanghai 200234, China, School of Electronic and Information Engineering Guangzhou City University of Technology, Guangzhou 510800, China
  • Jian Zhang Xpeedic Technology, Inc. Shanghai 201210, China
  • Chi Zhou Shanghai Engineering Research Center of Intelligent Education and Bigdata Shanghai Normal University, Shanghai 200234, China
  • Mei Song Tong Department of Electronic Science and Technology Tongji University, Shanghai 201804, China

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https://doi.org/10.13052/2024.ACES.J.400803

关键词:

diffraction tomography (DT), generative adversarial network (GAN), inverse scattering, limited angle

摘要

In the context of long-distance detection and obstacle occlusion, the limited observation angle of electromagnetic imaging poses significant challenges for accurate reconstruction. To address this issue, we propose a hybrid electromagnetic reconstruction algorithm based on a generative adversarial network (GAN). This algorithm utilizes the diffraction tomography (DT) method to generate an initial image, which serves as input for the GAN. Through adversarial training between the generator and the discriminator, the algorithm produces a reconstructed image with enhanced accuracy. Firstly, unlike complete learning-based reconstruction methods that rely solely on scattering field data, our approach effectively integrates both scattering characteristics and a priori information from the DT image model, thus improving the accuracy and generalizability of the neural network. Secondly, compared to other linear approximation algorithms, the DT algorithm incorporates fast Fourier transform (FFT) to enhance computational efficiency. Thirdly, this study employs a Fourier spatial data extrapolation technique to mitigate the limitations of insufficient data and improve imaging fidelity. Numerical simulations demonstrate that even at a narrow observation angle of 900, the proposed algorithm exhibits excellent reconstruction performance and notable generalization ability.

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Chun Xia Yang received the Ph.D. degree in electronic science and technology from Tongji University, Shanghai, China, in 2017. During her doctoral studies, she also conducted research at the Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Champaign, IL, USA as a visiting student between 2014 and 2016. She is currently an associate professor at the Department of Communication Engineering, Shanghai Normal University, Shanghai, China. Her ongoing research interests primarily revolve around electromagnetic inverse scattering for imaging and computational electromagnetics.

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Xirui Yang received her B.S. degree in Communication Engineering and M.S. degree in Electronic Information from Shanghai Normal University, Shanghai, China, in 2021 and 2024, respectively. She is currently affiliated with the School of Electronic and Information Engineering, Guangzhou City University of Technology, Guangzhou, China. Her research focuses primarily on electromagnetic inverse scattering.

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Jian Zhang received his B.S. degree in Electronics Science and Technology and his Ph.D. degree in Control Science and Engineering from Tongji University, Shanghai, China, in 2014 and 2020, respectively. He is currently working as an Engineer at Xpeedic Technology, Inc., Shanghai, China. His research mainly focuses on multi-physics numerical simulation techniques.

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Chi Zhou received the M.S. degree in Electronic Information from Shanghai Normal University, Shanghai, China, in 2025. He is currently affiliated with Wenyin Cloud Computing Co., Ltd, Shanghai, China. His research mainly focuses on electromagnetic inverse scattering.

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Mei Song Tong received the B.S. and M.S. Degrees from Huazhong University of Science and Technology, Wuhan, China, respectively, and Ph.D. degree from Arizona State University, Tempe, Arizona, USA, all in electrical engineering. He is currently the Distinguished Professor and Head of Department of Electronic Science and Technology, and Vice Dean of College of Microelectronics, Tongji University, Shanghai, China. He has also held an adjunct professorship at the University of Illinois at Urbana-Champaign, Urbana, Illinois, USA, and an honorary professorship at the University of Hong Kong, China. He has published more than 700 papers in refereed journals and conference proceedings and co-authored six books or book chapters. His research interests include electromagnetic field theory, antenna theory and design, simulation and design of RF/microwave circuits and devices, interconnect and packaging analysis, inverse electromagnetic scattering for imaging, and computational electromagnetics.

Prof. Tong is a Fellow of the Electromagnetics Academy, Fellow of the Japan Society for the Promotion of Science (JSPS), and Senior Member (Commission B) of the USNC/URSI. He has been the chair of Shanghai Chapter since 2014 and the chair of SIGHT committee in 2018, respectively, in IEEE Antennas and Propagation Society. He has served as an associate editor or guest editor for several well-known international journals, including IEEE Antennas and Propagation Magazine, IEEE Transactions on Antennas and Propagation, IEEE Transactions on Components, Packaging and Manufacturing Technology, International Journal of Numerical Modeling: Electronic Networks, Devices and Fields, Progress in Electromagnetics Research, and Journal of Electromagnetic Waves and Applications, etc. He also frequently served as a session organizer/chair, technical program committee member/chair, and general chair for some prestigious international conferences. He was the recipient of a Visiting Professorship Award from Kyoto University, Japan, in 2012, and from University of Hong Kong, China, 2013. He advised and coauthored 15 papers that received the Best Student Paper Award from different international conferences. He was the recipient of the Travel Fellowship Award of USNC/URSI for the 31th General Assembly and Scientific Symposium (GASS) in 2014, Advance Award of Science and Technology of Shanghai Municipal Government in 2015, Fellowship Award of JSPS in 2016, Innovation Award of Universities’ Achievements of Ministry of Education of China in 2017, Innovation Achievement Award of Industry-Academia-Research Collaboration of China in 2019, “Jinqiao” Award of Technology Market Association of China in 2020, Baosteel Education Award of China in 2021, Carl Friedrich von Siemens Research Award of the Alexander von Humboldt Foundation of Germany in 2023, and Technical Achievement Award of Applied Computational Electromagnetic Society (ACES) of USA in 2024. In 2018, he was selected as the Distinguished Lecturer (DL) of IEEE Antennas and Propagation Society for 2019-2022.

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已出版

2025-08-30

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[1]
C. X. . Yang, X. . Yang, J. . Zhang, C. . Zhou, 和 M. S. . Tong, 《An Electromagnetic Imaging Algorithm Based on Generative Adversarial Network for Limited Observation Angle》, ACES Journal, 卷 40, 期 08, 页 702–713, 8月 2025.

期

2025: Vol 40 Iss 8

栏目

General Submission

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