Antenna Shape Modeling based on Histogram of Oriented Gradients Feature

Authors

  • Hai-Ying Luo School of Physics University of Electronic Science and Technology of China, Chengdu, 611731, China
  • Wen-Hao Su 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
  • Wei Shao School of Physics University of Electronic Science and Technology of China, Chengdu, 611731, China

DOI:

https://doi.org/10.13052/2023.ACES.J.380908

Keywords:

B-spline curve, microstrip antenna, shape modeling, support vector machine

Abstract

A least square support vector machine (SVM) model is proposed for shape modeling of slot antennas. The slot image is mapped into the electromagnetic response by the SVM model. A modified shape-changing technique is also proposed to describe the antenna geometry by the quadratic uniform B-spline curve and generate the slot images. In the model, the histogram of oriented gradients feature is extracted from the slot images to show the appearance and shape of the slot. The relationship between the histogram of oriented gradient features and the electromagnetic responses is preliminarily built on SVM and the transfer function. Then a radial basis function network is used for error correction. The effectiveness of the proposed model is confirmed with an example of a tri-band microstrip-fed slot antenna. Compared with the convolutional neural network (CNN), the feature extracted by CNN is substituted by the histogram of oriented gradients feature, and the proposed model shows the same accuracy and the improvement of training efficiency.

Downloads

Download data is not yet available.

Author Biographies

Hai-Ying Luo, School of Physics University of Electronic Science and Technology of China, Chengdu, 611731, China

Hai-Ying Luo received the B.S. degree from the University of Electronic Science and Technology of China (UESTC), Chengdu, China, in 2017, where he is currently pursuing the Ph.D. degree in radio physics.

His current research interest is computational electromagnetics.

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 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.

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 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, 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, 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.

References

H. M. E. Misilmani, T. Naous, and S. K. A. Khatib, “A review on the design and optimization of antennas using machine learning algorithms and techniques,” Int. J. RF Microw. Comput.-Aided Eng., vol. 30, no. 10, p. e22356, Oct. 2020.

L.-Y. Xiao, W. Shao, F.-L. Jin, and B.-Z. Wang, “Multiparameter modeling with ANN for antenna design,” IEEE Trans. Antennas Propag., vol. 66, no. 7, pp. 3718-3723, July 2018.

T. Khan and C. Roy, “Prediction of slot-position and slot-size of a microstrip antenna using support vector regression,” Int. J. RF Microw. Comput.-Aided Eng., vol. 29, no. 3, p. e21623, Mar. 2019.

Y. Kim, S. Keely, J. Ghosh, and H. Ling, “Application of artificial neural networks to broadband antenna design based on a parametric frequency model,” IEEE Trans. Antennas Propag., vol. 55, no. 3, pp. 669-674, Mar. 2007.

F. Feng, C. Zhang, J. Ma, and Q.-J. Zhang, “Parametric modeling of EM behavior of microwave components using combined neural networks and pole-residue-based transfer functions,” IEEE Trans. Microw. Theory Techn., vol. 64, no. 1, pp. 60-77, Jan. 2016.

F. Feng, V.-M.-R. Gongal-Reddy, C. Zhang, J. Ma, and Q.-J. Zhang, “Parametric modeling of microwave components using adjoint neural networks and pole-residue transfer functions with EM sensitivity analysis,” IEEE Trans. Microw. Theory Techn., vol. 65, no. 6, pp. 1955-1975, June 2017.

J. P. Jacobs, “Accurate modeling by convolutional neural-network regression of resonant frequencies of dual-band pixelated microstrip antenna,” IEEE Antennas Wireless Propag. Lett., vol. 20, no. 12, pp. 2417-2421, Dec. 2021.

H.-Y. Luo, W. Shao, X. Ding, B.-Z. Wang, and X. Cheng, “Shape modeling of microstrip filters based on convolutional neural network,” IEEE Microw. Wireless Compon. Lett., vol. 32, no. 9, pp. 1019-1022, Sep. 2022.

N. Dalal and B. Triggs, “Histograms of oriented gradients for human detection,” IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit., San Diego, CA, USA, vol. 1, pp. 886-893, 2005.

R. C. Gonzalez and R. E. Woods, Digital Image Processing, USA: Prentice Hall, Upper Saddle River, NJ, 2002.

S. Xu, X. An, X. Qiao, L. Zhu, and L. Li, “Multi-output least-squares support vector regression machines,” Pattern Recognit. Lett., vol. 34, no. 9, pp. 1078-1084, July 2013.

B. Gustavsen and A. Semlyen, “Rational approximation of frequency domain responses by vector fitting,” IEEE Trans. Power Del., vol. 14, no. 3, pp. 1052-1061, July 1999.

K. D. Xu, Y. H. Zhang, R. J. Spiegel, Y. Fan, W. T. Joines, and Q. H. Liu, “Design of a stub-loaded ring-resonator slot for antenna applications,” IEEE Trans. Antennas Propag., vol. 63, no. 2, pp. 517-524, Feb. 2015.

J. Snoek, H. Larochelle, and R. P. Adams, “Practical Bayesian optimization of machine learning algorithms” in Adv. in Neural Inf. Process. Syst. 25, USA: Curran Associates Inc., Red Hook, NY, pp. 2951-2959, 2012.

R. L. Haupt and D. H. Werner, Genetic Algorithms in Electromagnetics, USA: Wiley, Hoboken, NJ, 2007.

Downloads

Published

2023-09-30

How to Cite

[1]
H.-Y. . Luo, W.-H. . Su, H. . Ou, S.-J. . Zhang, and W. . Shao, “Antenna Shape Modeling based on Histogram of Oriented Gradients Feature”, ACES Journal, vol. 38, no. 09, pp. 687–694, Sep. 2023.

Issue

2023: Vol 38 Iss 9

Section

Special Issue on ACES-China 2022 Conference