摘要
针对超表面全息成像技术中存在的工作频段窄、近场成像效率低等问题,本文提出了消色散宽频超表面全息成像优化原理及模型,提出了基于深度图像先验的深度学习网络模型用于单目标的被动式超表面全息图设计,实现了消色散宽频超表面全息成像。数值仿真和实验结果均证明,所设计的全息成像器件可以在9 GHz~11 GHz频段内实现良好的消色散成像效果,在全息成像、宽频功能器件设计等领域具有极大的应用潜力。
Aiming at the problems of narrow working frequency band and low near field imaging efficiency in metasurface holographic imaging technology,this paper proposed the principle and model of optimization of achromatic broadband metasurface hologram imaging.A deep learning network model based on the depth image prior(DIP)is proposed for single-target passive metasurface hologram design,and achromatic broadband metasurface hologram imaging is achieved.Numerical simulation and experimental results have proved that the designed holographic imaging device can achieve good achromatic imaging effect in the 9 GHz~11 GHz frequency band,and has great potential application in the field of holographic imaging and broadband functional device design.
作者
李瑞琛
邹毅军
陈天航
郑斌
蔡通
Li Ruichen;Zou Yijun;Chen Tianhang;Zheng Bin;Cai Tong(College of Information Science&Electronic Engineering,Zhejiang University,Hangzhou,Zhejiang 310027,China;Chinese Aeronautical Establishment,Beijing 100029,China;Air Force Engineering University,Xi’an,Shaanxi 710100,China)
出处
《光电工程》
CAS
CSCD
北大核心
2023年第8期90-98,共9页
Opto-Electronic Engineering
基金
国家自然科学基金项目(62071423)。
关键词
全息成像
超表面
消色散
holographic imaging
metasurface
achromatic
