350 rub
Journal Radioengineering №5 for 2024 г.
Article in number:
Special aspects of patch antennas synthesis using genetic algorithm
Type of article: scientific article
DOI: https://doi.org/10.18127/j00338486-202405-15
UDC: 621.396.677
Authors:

M.M. Migalin1, V.A. Obukhovets2

1,2 Southern Federal University (Taganrog, Russia)

1 migalin@sfedu.ru

Abstract:

Microstrip-fed patch antenna synthesis can be performed using one of the numerous optimization algorithms, such as a genetic algorithm (GA). VBA or IronPython script engines implemented in modern CAD systems make it possible to implement GA. However, the capabilities of these languages for processing matrix data are limited. The use of a MATLAB environment script could combine the capabilities of MATLAB and CAD for electromagnetic modelling. It would make it possible to generate chromosomes of individuals of a given length, build antenna models in CAD that reflect the genetic code of individuals, process modelling results in MATLAB, carry out crossing over and mutations with a given probability for obtaining patch antennas that provide a user-specified value of the goal function.

The primary purpose of this work is to propose a script in the MATLAB environment that allows complete automation of microstrip antennas' structural synthesis in MATLAB - CAD using GA, as well as to study GA selection methods and their influence on the results of this algorithm.

As a result, a MATLAB script has been developed, combining the capabilities of electromagnetic modelling CAD and the MATLAB environment for processing matrix data for fully automated synthesis of the microstrip-fed patch antenna. It is shown that the proposed script randomly generates an initial population, creates a CAD model corresponding to each individual, determines the value of the goal function for each individual, performs crossing over and mutations, and then iteratively repeats the above actions until the GA convergence condition is satisfied. This paper highlights that the GA convergence speed depends on the selection method chosen before crossing over. Recommendations for choosing a selection method are formulated. The results of synthesizing a microstrip antenna with a frequency band 5.2 times greater than the frequency band of the reference antenna are presented.

The presented script combines the capabilities of electromagnetic modelling CAD and MATLAB to fully automate the process of structural synthesis of microstrip antennas with a given frequency response and the main lobe direction of the radiation pattern.

Pages: 129-135
For citation

Migalin M.M., Obukhovets V.A. Special aspects of patch antennas synthesis using genetic algorithm. Radiotekhnika. 2024. V. 88.
№ 5. P. 123−129. DOI: https://doi.org/10.18127/j00338486-202405-14 (In Russian)

References
  1. Kamenskov A.E. Iskusstvennye nejronnye seti dlja proektirovanija i analiza antenn. Sb. nauch. trudov II Mezhdunar. nauch.-praktich. konf. «Infokommunikacionnye tehnologii: aktual'nye voprosy cifrovoj jekonomiki» (g. Ekaterinburg, 26–27 janvarja 2022 g.). 2022. S. 117–122 (in Russian).
  2. Borodulin R.Ju., Luk'janov N.O., Sosunov B.V. Konstrukcionnyj sintez shirokopolosnogo ploskostnogo izluchatelja geneticheskim algoritmom. Informacija i kosmos. 2014. № 4. S. 4–8 (in Russian).
  3. Tung L., Manh L., Ngoc C., Beccaria M., Pirinoli P. Automated design of microstrip patch antenna using ant colony optimization. 2019 International Conference on Electromagnetics in Advanced Applications. 2019. P. 0587–0590. DOI: 10.1109/ICEAA.2019.8879031.
  4. Abdrahmanova G.I. Modelirovanie SShP-antenn na osnove algoritmov optimizacii. Sovremennye problemy nauki i obrazovanija. 2013. № 4. URL: https://science-education.ru/ru/article/view?id=9849 (data obrashhenija: 11.10.2023) (in Russian).
  5. Goudos S., Boursianis A., Mohamed A., Salucci M., Koulouridis S., Christodoulou C. Wideband Antenna Design for 5G mmWave Applications Using Enhanced Adaptive Differential Evolution. 2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting. 2022. P. 63–64. DOI: 10.1109/AP-S/USNC-URSI47032.2022.9886187.
  6. Mounir B., Reddaf А., Kacha А., et al. Design and optimization of miniaturized microstrip patch antennas using a genetic algorithm. Electronics 11. 2022. № 14. P. 2123.
  7. Migalin M.M., Koshkid'ko V.G., Demshevsky V.V. Application of macros for automated performance of the same type operations when simulating SIW-based slotted waveguide antennas in Ansys HFSS CAD. Antennas. 2023. № 1. P. 63–77. DOI: https://doi.org/ 10.18127/j03209601-202301-04 (in Russian)
  8. Balanis C.A. Antenna theory: analysis and design. Wiley. 2016. 1095 p.
  9. Gladkov L.A., Kurejchik V.V., Kurejchik V.M. Geneticheskie algoritmy: Uchebnik. Izd-e 2-e, ispr. i dop. M.: OOO Izdatel'skaja firma «Fiziko-matematicheskaja literatura». 2010. 366 s. (in Russian)
  10. Migalin M., Obukhovets V. MM-wave patch antenna synthesis using genetic algorithm. 2023 Radiation and Scattering of Electromagnetic Waves. 2023. P. 212–215. DOI: 10.1109/RSEMW58451.2023.10202070.
  11. Haupt R., Werner D. Genetic Algorithms in Electromagnetics. Hoboken. NJ. USA: Wiley. 2007.
Date of receipt: 26.01.2024
Approved after review: 31.01.2024
Accepted for publication: 29.04.2024