(Peer-Reviewed) Ka-Band metalens antenna empowered by physics-assisted particle swarm optimization (PA-PSO) algorithm
Shibin Jiang 江世斌 ¹, Wenjun Deng 邓文俊 ¹, Zhanshan Wang 王占山 ², Xinbin Cheng 程鑫彬 ², Din Ping Tsai 蔡定平 ³, Yuzhi Shi 施宇智 ², Weiming Zhu 朱伟明 ¹
¹ School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu 610051, China
中国 成都 电子科技大学 光电科学与工程学院
² Institute of Precision Optical Engineering, School of Physics Science and Engineering, Tongji University, Shanghai 200092, China
中国 上海 同济大学物理科学与工程学院 精密光学工程技术研究所
³ Department of Electrical Engineering, City University of Hong Kong, Hong Kong 999077, China
中国 香港 香港城市大学 电机工程学系
Opto-Electronic Science, 2024-07-26
Abstract
Design of multiple-feed lens antennas requires multivariate and multi-objective optimization processes, which can be accelerated by PSO algorithms. However, the PSO algorithm often fails to achieve optimal results with limited computation resources since spaces of candidate solutions are quite large for lens antenna designs.
This paper presents a design paradigm for multiple-feed lens antennas based on a physics-assisted particle swarm optimization (PA-PSO) algorithm, which guides the swarm of particles based on laws of physics. As a proof of concept, a design of compact metalens antenna is proposed, which measures unprecedented performances, such as a field of view at ±55°, a 21.7 dBi gain with a flatness within 4 dB, a 3-dB bandwidth >12°, and a compact design with af-number of 0.2.
The proposed PA-PSO algorithm reaches the optimal results 6 times faster than the ordinary PSO algorithm, which endows promising applications in the multivariate and multi-objective optimization processes, including but not limited to metalens antenna designs.
Separation and identification of mixed signal for distributed acoustic sensor using deep learning
Huaxin Gu, Jingming Zhang, Xingwei Chen, Feihong Yu, Deyu Xu, Shuaiqi Liu, Weihao Lin, Xiaobing Shi, Zixing Huang, Xiongji Yang, Qingchang Hu, Liyang Shao
Opto-Electronic Advances
2025-11-25
