Araştırma Makalesi
BibTex RIS Kaynak Göster
Yıl 2021, Cilt: 1 Sayı: 2, 160 - 164, 30.12.2021

Öz

Kaynakça

  • D.G. Berry, R.G. Malech, and W.A. Kennedy, The reflectarray antenna, IEEE Trans Antennas Propagat 11 (1963), 645–651.
  • P. Mahouti, “Application of artificial intelligence algorithms on modeling of reflection phase characteristics of a nonuniform reflectarray element.” International Journal of Numerical Modelling: Electronic Networks, Devices and Fields 33, no. 2 (2020): e2689.
  • D.M. Pozar, S.D. Targonski, and H.D. Syrigos, Design of millimeter wave microstrip reflectarrays, IEEE Trans Antennas Propagat 45 (1997), 287–297. J. Huang and J.A. Encinar, Reflectarray antennas, John Wiley & Sons, Inc., Hoboken, NJ, USA, 2007. ISBN:978-0-470- 08491-4.
  • A. Belen, F. Güneş, M. A. Belen, and P. Mahouti. “3D printed wideband flat gain multilayer nonuniform reflectarray antenna for X‐band applications.” International Journal of Numerical Modelling: Electronic Networks, Devices and Fields 33, no. 6 (2020): e2753.
  • M. Mahouti, N. Kuskonmaz, P. Mahouti, M. A. Belen, and M. Palandoken, “Artificial neural network application for novel 3D printed nonuniform ceramic reflectarray antenna,” International Journal of Numerical Modelling: Electronic Networks, Devices and Fields, 33(6), e2746, 2020.
  • J. Jingon. "Machine learning-based antenna selection in wireless communications." IEEE Communications Letters 20, no. 11 (2016): 2241-2244.
  • S. Koziel "Low-cost data-driven surrogate modeling of antenna structures by constrained sampling." IEEE Antennas and Wireless Propagation Letters 16 (2016): 461-464.
  • S. Koziel, and A. Pietrenko-Dabrowska. "Performance-based nested surrogate modeling of antenna input characteristics." IEEE Transactions on Antennas and Propagation 67, no. 5 (2019): 2904-2912.
  • H. Kalayci, U. E. Ayten, and P. Mahouti. "Ensemble‐based surrogate modeling of microwave antennas using XGBoost algorithm." International Journal of Numerical Modelling: Electronic Networks, Devices and Fields (2021): e2950.
  • S. Koziel, N. Çalık, P. Mahouti, and M A. Belen. "Accurate Modeling of Antenna Structures by Means of Domain Confinement and Pyramidal Deep Neural Networks." IEEE Transactions on Antennas and Propagation (2021).
  • S. Koziel, P. Mahouti, N. Calik, M. A. Belen, and S. Szczepanski. "Improved Modeling of Microwave Structures Using Performance-Driven Fully-Connected Regression Surrogate." IEEE Access 9 (2021): 71470-71481.
  • M. Bereket, A. Belen, and M. A. Belen, “Yapay Sinir Ağı Tabanlı Mikroşerit Yansıtıcı Dizi Anten Birim Hücre Tasarımı” 1st International Congress on Artificial Intelligence and Data Science, 2021
  • S. Finich, N. A. Touhami, and A. Farkhsi, “Design and analysis of different shapes for unit-cell reflectarrray antenna”, Procedia Engineering 181, pp. 526-537, 2017.
  • H. Bodur, and S.Çimen, “X-bant uygulamalar için tek katmanlı değişken birim eleman boyutlu yansıtıcı dizi anten tasarımı,” Journal of the Faculty of Engineering and Architecture of Gazi University 34:4 (2019) 1861-1869
  • A. Belen, F. Günes ̧ M. A. Belen, P. Mahouti, “3D printed wideband flat gain multilayer nonuniform reflectarray antenna for X- band applications,” Int J Numer Model El. 2020;e2753. https://doi.org/10.1002/jnm.2753

Artificial Neural Network Based Microstrip Reflectarray Unit Element Design

Yıl 2021, Cilt: 1 Sayı: 2, 160 - 164, 30.12.2021

Öz

Microstrip reflectarray antennas (RAs) are designs that can achieve equivalent performance of parabolic reflector, but with simple and light electromagnetic and mechanical structures. The challenging problem in design of RA is the fast and accurate modelling of the unit element for the array optimization. 3D EM simulators are computationally very ineffective, thus in this study artificial neural network based unit element modelling for characterization of the reflection phase of the unit element in terms of its geometry, and operation frequency is studied. For this mean, a Malta Cross shaped design for X-band applications is taken into the consideration using Multilayer Perceptron (MLP) neural network trained the 3D CST microwave Studio simulator data. Validation of the MLP model is also worked out successfully with the 3D CST data. By this mean, a continuous function is obtained for the reflection phase of the unit element with respect to the variation of geometrical design parameters and operation frequency had been achieved which can be used for a design optimization process fast as analytical approach design while being accurate as 3D EM simulator tools.

Kaynakça

  • D.G. Berry, R.G. Malech, and W.A. Kennedy, The reflectarray antenna, IEEE Trans Antennas Propagat 11 (1963), 645–651.
  • P. Mahouti, “Application of artificial intelligence algorithms on modeling of reflection phase characteristics of a nonuniform reflectarray element.” International Journal of Numerical Modelling: Electronic Networks, Devices and Fields 33, no. 2 (2020): e2689.
  • D.M. Pozar, S.D. Targonski, and H.D. Syrigos, Design of millimeter wave microstrip reflectarrays, IEEE Trans Antennas Propagat 45 (1997), 287–297. J. Huang and J.A. Encinar, Reflectarray antennas, John Wiley & Sons, Inc., Hoboken, NJ, USA, 2007. ISBN:978-0-470- 08491-4.
  • A. Belen, F. Güneş, M. A. Belen, and P. Mahouti. “3D printed wideband flat gain multilayer nonuniform reflectarray antenna for X‐band applications.” International Journal of Numerical Modelling: Electronic Networks, Devices and Fields 33, no. 6 (2020): e2753.
  • M. Mahouti, N. Kuskonmaz, P. Mahouti, M. A. Belen, and M. Palandoken, “Artificial neural network application for novel 3D printed nonuniform ceramic reflectarray antenna,” International Journal of Numerical Modelling: Electronic Networks, Devices and Fields, 33(6), e2746, 2020.
  • J. Jingon. "Machine learning-based antenna selection in wireless communications." IEEE Communications Letters 20, no. 11 (2016): 2241-2244.
  • S. Koziel "Low-cost data-driven surrogate modeling of antenna structures by constrained sampling." IEEE Antennas and Wireless Propagation Letters 16 (2016): 461-464.
  • S. Koziel, and A. Pietrenko-Dabrowska. "Performance-based nested surrogate modeling of antenna input characteristics." IEEE Transactions on Antennas and Propagation 67, no. 5 (2019): 2904-2912.
  • H. Kalayci, U. E. Ayten, and P. Mahouti. "Ensemble‐based surrogate modeling of microwave antennas using XGBoost algorithm." International Journal of Numerical Modelling: Electronic Networks, Devices and Fields (2021): e2950.
  • S. Koziel, N. Çalık, P. Mahouti, and M A. Belen. "Accurate Modeling of Antenna Structures by Means of Domain Confinement and Pyramidal Deep Neural Networks." IEEE Transactions on Antennas and Propagation (2021).
  • S. Koziel, P. Mahouti, N. Calik, M. A. Belen, and S. Szczepanski. "Improved Modeling of Microwave Structures Using Performance-Driven Fully-Connected Regression Surrogate." IEEE Access 9 (2021): 71470-71481.
  • M. Bereket, A. Belen, and M. A. Belen, “Yapay Sinir Ağı Tabanlı Mikroşerit Yansıtıcı Dizi Anten Birim Hücre Tasarımı” 1st International Congress on Artificial Intelligence and Data Science, 2021
  • S. Finich, N. A. Touhami, and A. Farkhsi, “Design and analysis of different shapes for unit-cell reflectarrray antenna”, Procedia Engineering 181, pp. 526-537, 2017.
  • H. Bodur, and S.Çimen, “X-bant uygulamalar için tek katmanlı değişken birim eleman boyutlu yansıtıcı dizi anten tasarımı,” Journal of the Faculty of Engineering and Architecture of Gazi University 34:4 (2019) 1861-1869
  • A. Belen, F. Günes ̧ M. A. Belen, P. Mahouti, “3D printed wideband flat gain multilayer nonuniform reflectarray antenna for X- band applications,” Int J Numer Model El. 2020;e2753. https://doi.org/10.1002/jnm.2753
Toplam 15 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Yapay Zeka
Bölüm Research Articles
Yazarlar

Mehmet Bereket Bu kişi benim

Aysu Belen

Mehmet Ali Belen

Yayımlanma Tarihi 30 Aralık 2021
Gönderilme Tarihi 1 Aralık 2021
Yayımlandığı Sayı Yıl 2021 Cilt: 1 Sayı: 2

Kaynak Göster

IEEE M. Bereket, A. Belen, ve M. A. Belen, “Artificial Neural Network Based Microstrip Reflectarray Unit Element Design”, Journal of Artificial Intelligence and Data Science, c. 1, sy. 2, ss. 160–164, 2021.

All articles published by JAIDA are licensed under a Creative Commons Attribution 4.0 International License.

88x31.png