ML-Driven Optimisation of Luneburg Lens Design

Authors

  • Ravi Kumar Arya Xiangshan Laboratory, Zhongshan Institute of Changchun University of Science and Technology, Zhongshan, Guangdong – 528 400, China
  • Maxon Okramcha School of Physics, Changchun University of Science and Technology, Changchun – 130022, China
  • Anant Rajput School of Engineering, Jawaharlal Nehru University, New Delhi - 110 067, India
  • K.M. Mohan School of Engineering, Jawaharlal Nehru University, New Delhi - 110 067, India
  • Aditya Sharma School of Engineering, Jawaharlal Nehru University, New Delhi - 110 067, India
  • Amitanshu Raj Neti School of Engineering, Jawaharlal Nehru University, New Delhi - 110 067, India
  • Priyanshu Ganwani School of Engineering, Jawaharlal Nehru University, New Delhi - 110 067, India
  • Maifuz Ali Electronics and Communication Engineering, IIIT Narya Raipur, Chhattisgarh – 493 661, India
  • Ashwani Kumar School of Engineering, University of Delhi, New Delhi - 110 007 India

DOI:

https://doi.org/10.14429/dsj.20910

Keywords:

Luneburg lens antenna, X-band, Clustering algorithms, K-means, GRIN (Graded Index), ML (Machine Learning), Microwave engineering, Additive manufacturing technology

Abstract

Designing the properties of constant index shells in Luneburg lenses presents a significant challenge due to the inherent mathematical complexity. Although various methods have been proposed to address this issue, many are either overly complex or computationally intensive. However, recent machine learning (ML) advancements have revolutionized solutions to such engineering challenges. This study showcases how ML can streamline the design process for multishell Luneburg lenses, drastically reducing the required effort and computational resources. Our approach employs k-means clustering to determine the properties of the lens’s shells. To validate the effectiveness and reliability of our method, we compare simulated results with experimental measurements, demonstrating its accuracy and robustness.

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Published

2025-05-08

How to Cite

Kumar Arya, R., Okramcha, M., Rajput, A., Mohan, K., Sharma, A., Raj Neti, A., Ganwani, P., Ali, M., & Kumar, A. (2025). ML-Driven Optimisation of Luneburg Lens Design. Defence Science Journal, 75(3), 293–299. https://doi.org/10.14429/dsj.20910

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