Efficient Embedded Element Pattern Prediction via Machine Learning: A Case Study with Planar Non-Uniform Sub-Arrays

Nehir Berk Onat; Ignacio  Roldan; Francesco  Fioranelli; Alexander Yarovoy; Yanki Aslan

doi:10.23919/EuCAP57121.2023.10133770

Efficient Embedded Element Pattern Prediction via Machine Learning: A Case Study with Planar Non-Uniform Sub-Arrays

Nehir Berk Onat, Ignacio Roldan, Francesco Fioranelli, Alexander Yarovoy, Yanki Aslan

Microwave Sensing, Signals & Systems

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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Abstract

Efficient prediction of embedded element patterns (EEPs) is including the mutual coupling (MC) effects in the optimization of irregular planar arrays is studied for the first time in the literature. An ANN-based methodology is used to predict the pattern of each element in the whole visible space for a flexible planar array topology in milliseconds. The technique is proposed is validated on a 4-element planar non-uniform sub-array structure. Excellent accuracy on the EEP prediction while providing great efficiency in computational time and load in comparison to the full-wave simulations is demonstrated.

Original language	English
Title of host publication	Proceedings of the 2023 17th European Conference on Antennas and Propagation (EuCAP)
Publisher	IEEE
Pages	1-5
Number of pages	5
ISBN (Electronic)	9788831299077
ISBN (Print)	978-1-6654-7541-9
DOIs	https://doi.org/10.23919/EuCAP57121.2023.10133770
Publication status	Published - 2023
Event	EuCAP 2023: 17th European Conference on Antennas and Propagation (EuCAP) - Florence, Italy Duration: 26 Mar 2023 → 31 Mar 2023 Conference number: 17th

Publication series

Name	17th European Conference on Antennas and Propagation, EuCAP 2023

Conference

Conference	EuCAP 2023
Country/Territory	Italy
City	Florence
Period	26/03/23 → 31/03/23

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

artificial neural network (ANN)
embedded element pattern (EEP)
irregular antenna array
mutual coupling (MC)
phased array antenna

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10.23919/EuCAP57121.2023.10133770

Efficient_Embedded_Element_Pattern_Prediction_via_Machine_Learning_A_Case_Study_with_Planar_Non-Uniform_Sub-ArraysFinal published version, 987 KB

Cite this

Onat, N. B., Roldan, I., Fioranelli, F., Yarovoy, A., & Aslan, Y. (2023). Efficient Embedded Element Pattern Prediction via Machine Learning: A Case Study with Planar Non-Uniform Sub-Arrays. In Proceedings of the 2023 17th European Conference on Antennas and Propagation (EuCAP) (pp. 1-5). (17th European Conference on Antennas and Propagation, EuCAP 2023). IEEE. https://doi.org/10.23919/EuCAP57121.2023.10133770

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title = "Efficient Embedded Element Pattern Prediction via Machine Learning: A Case Study with Planar Non-Uniform Sub-Arrays",

abstract = "Efficient prediction of embedded element patterns (EEPs) is including the mutual coupling (MC) effects in the optimization of irregular planar arrays is studied for the first time in the literature. An ANN-based methodology is used to predict the pattern of each element in the whole visible space for a flexible planar array topology in milliseconds. The technique is proposed is validated on a 4-element planar non-uniform sub-array structure. Excellent accuracy on the EEP prediction while providing great efficiency in computational time and load in comparison to the full-wave simulations is demonstrated.",

keywords = "artificial neural network (ANN), embedded element pattern (EEP), irregular antenna array, mutual coupling (MC), phased array antenna",

author = "Onat, {Nehir Berk} and Ignacio Roldan and Francesco Fioranelli and Alexander Yarovoy and Yanki Aslan",

note = "Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.; EuCAP 2023 : 17th European Conference on Antennas and Propagation (EuCAP) ; Conference date: 26-03-2023 Through 31-03-2023",

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doi = "10.23919/EuCAP57121.2023.10133770",

language = "English",

isbn = "978-1-6654-7541-9",

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Onat, NB , Roldan, I , Fioranelli, F , Yarovoy, A & Aslan, Y 2023, Efficient Embedded Element Pattern Prediction via Machine Learning: A Case Study with Planar Non-Uniform Sub-Arrays. in Proceedings of the 2023 17th European Conference on Antennas and Propagation (EuCAP). 17th European Conference on Antennas and Propagation, EuCAP 2023, IEEE, pp. 1-5, EuCAP 2023, Florence, Italy, 26/03/23. https://doi.org/10.23919/EuCAP57121.2023.10133770

Efficient Embedded Element Pattern Prediction via Machine Learning: A Case Study with Planar Non-Uniform Sub-Arrays. / Onat, Nehir Berk ; Roldan, Ignacio ; Fioranelli, Francesco et al.
Proceedings of the 2023 17th European Conference on Antennas and Propagation (EuCAP). IEEE, 2023. p. 1-5 (17th European Conference on Antennas and Propagation, EuCAP 2023).

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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AB - Efficient prediction of embedded element patterns (EEPs) is including the mutual coupling (MC) effects in the optimization of irregular planar arrays is studied for the first time in the literature. An ANN-based methodology is used to predict the pattern of each element in the whole visible space for a flexible planar array topology in milliseconds. The technique is proposed is validated on a 4-element planar non-uniform sub-array structure. Excellent accuracy on the EEP prediction while providing great efficiency in computational time and load in comparison to the full-wave simulations is demonstrated.

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KW - embedded element pattern (EEP)

KW - irregular antenna array

KW - mutual coupling (MC)

KW - phased array antenna

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Onat NB , Roldan I , Fioranelli F , Yarovoy A , Aslan Y. Efficient Embedded Element Pattern Prediction via Machine Learning: A Case Study with Planar Non-Uniform Sub-Arrays. In Proceedings of the 2023 17th European Conference on Antennas and Propagation (EuCAP). IEEE. 2023. p. 1-5. (17th European Conference on Antennas and Propagation, EuCAP 2023). doi: 10.23919/EuCAP57121.2023.10133770

Efficient Embedded Element Pattern Prediction via Machine Learning: A Case Study with Planar Non-Uniform Sub-Arrays

Abstract

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Keywords

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