Parametric Modeling for Curved Slots of Vivaldi Antenna Based on Artificial Neural Network

Authors

  • Wen-Hao Su School of Physics University of Electronic Science and Technology of China, Chengdu, 611731, China
  • Wei Shao School of Physics University of Electronic Science and Technology of China, Chengdu, 611731, China
  • Haiyan Ou School of Physics University of Electronic Science and Technology of China, Chengdu, 611731, China
  • Sheng-Jun Zhang National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing, 100076, China

DOI:

https://doi.org/10.13052/2023.ACES.J.380903

Keywords:

Artificial neural network, cubic spline interpolation, parametric modeling, Vivaldi antenna

Abstract

This paper proposes an artificial neural network (ANN) model based on parametric modeling for curved slots of the Vivaldi antenna. A more effective processing method is achieved by feeding ANN with the point positions that produce curved edges via cubic spline interpolation rather than the picture of metallic patches. The predicted results of ANN, including S-parameter and gain, agree well with those from the full-wave simulation. With the trained model, a Vivaldi antenna with the lower cut-off frequency is optimized by the multi-objective genetic algorithm.

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Author Biographies

Wen-Hao Su, School of Physics University of Electronic Science and Technology of China, Chengdu, 611731, China

Wen-Hao Su received the B.S. degree from the University of Electronic Science and Technology of China (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.

Wei Shao, School of Physics University of Electronic Science and Technology of China, Chengdu, 611731, 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.

Haiyan Ou, School of Physics University of Electronic Science and Technology of China, Chengdu, 611731, China

Haiyan Ou received the B.E. degree in electrical engineering from UESTC in 2000, and received Ph.D. degrees in optical engineering from Zhejiang University in 2009.

She joined UESTC in 2009 and is now an associate professor there. From 2010 to 2011, she was a visiting scholar in the department of Engineering, Cambridge University, UK. From 2012 to 2013, she was a post-doc in the Department of Electrical and Electronic Engineering, the University of Hong Kong. Her research interests include computational electromagnetics, microwave photonics, and digital holography.

Sheng-Jun Zhang, National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing, 100076, China

Sheng-Jun Zhang received a 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 interests 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.

References

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Published

2023-09-30

How to Cite

[1]
W.-H. . Su, W. . Shao, H. . Ou, and S.-J. . Zhang, “Parametric Modeling for Curved Slots of Vivaldi Antenna Based on Artificial Neural Network”, ACES Journal, vol. 38, no. 09, pp. 646–651, Sep. 2023.

Issue

2023: Vol 38 Iss 9

Section

Special Issue on ACES-China 2022 Conference