Neural Network Modeling for the Reduction of Scattering Grating Lobes of Arrays

Authors

  • Zhi-Xian Liu School of Physics University of Electronic Science and Technology of China Chengdu, China
  • Wen-Hao Su School of Physics University of Electronic Science and Technology of China Chengdu, China
  • Sheng-Jun Zhang National Key Laboratory of Science & Technology on Test Physics and Numerical Mathematics
  • Wei Shao School of Physics University of Electronic Science and Technology of China Chengdu, China

DOI:

https://doi.org/10.13052/2023.ACES.J.380901

Keywords:

Artificial neural network, metal wall, radar cross-section, scattering grating lobe

Abstract

The monostatic radar cross-section (RCS) of an array is seriously deteriorated by the scattering grating lobe. In this paper, the scattering grating lobe of an array is suppressed by metal walls around elements. The artificial neural network with Fourier series-based transfer functions is used to accelerate the design process. A 1×8 array with the patch element operating in the range from 9.4 to 10.6 GHz is studied. The monostatic RCS of the array with designed metal walls is compared with that of the array with no metal wall. Simulated results show that the scattering grating lobe of the array with metal walls is suppressed by 5.8 dB at 12 GHz, and the change of radiation performance is acceptable. The design procedure is also available for other arrays with reduced scattering grating lobes.

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Author Biographies

Zhi-Xian Liu, School of Physics University of Electronic Science and Technology of China Chengdu, China

Zhi-Xian Liu received the B.S. degree in electronic information science and technology from the China West Normal University, Nanchong, China, in 2019. She is currently pursuing the Ph.D. degree in radio physics in University of Electronic Science and Technology of China (UESTC), Chengdu, China.

Her current research interest includes electromagnetic wave scattering and artificial intelligence.

Wen-Hao Su, School of Physics University of Electronic Science and Technology of China Chengdu, China

Wen-Hao Su received the B.S. degree from UESTC, Chengdu, China, in 2021, where he is currently pursuing the master’s degree in radio physics.

His current research interests include antenna design and computational electromagnetics.

Sheng-Jun Zhang, National Key Laboratory of Science & Technology on Test Physics and Numerical Mathematics

Sheng-Jun Zhang received the Ph.D. in science from Beijing University of Technology in 2001. From then on he joined the team in National Key Laboratory of Science & Technology on Test Physics and Numerical Mathematics. He is now professor of the laboratory, and his research interest include scattering of EM waves, EM effects of periodic structures such as FSS, PC and gratings, as well as modulation of scattering of materials and interaction of EM waves with plasmas, and IR radiation management.

He has published some papers in journals and conferences, in addition to patents and two books.

Wei Shao, School of Physics University of Electronic Science and Technology of China Chengdu, China

Wei Shao received the B.E. degree in electrical engineering from UESTC in 1998, and received M.Sc. and Ph.D. degrees in radio physics from UESTC in 2004 and 2006, respectively.

He joined UESTC in 2007 and is now a professor there. From 2010 to 2011, he was a visiting scholar in the Electromagnetic Communication Laboratory, Pennsylvania State University, State College, PA. From 2012 to 2013, he was a visiting scholar in the Department of Electrical and Electronic Engineering, the University of Hong Kong. His research interests include computational electromagnetics and antenna design.

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Published

2023-09-30

How to Cite

[1]
Z.-X. . Liu, W.-H. . Su, S.-J. . Zhang, and W. . Shao, “Neural Network Modeling for the Reduction of Scattering Grating Lobes of Arrays”, ACES Journal, vol. 38, no. 09, pp. 633–637, Sep. 2023.

Issue

2023: Vol 38 Iss 9

Section

Special Issue on ACES-China 2022 Conference