Review of wavefront sensing technology in adaptive optics based on deep learning

Q4 Engineering
Liang Ziqiang, Li Xinyang, Gao Zeyu, Jia Qiwang
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引用次数: 1

Abstract

Wavefront sensing is an important part of adaptive optics system, which plays a key role in the fields of ground-based telescopes, laser transmission in atmosphere, wireless optical communication, laser nuclear fusion, and freeform surface optical measurement etc. Meanwhile, as a general advanced technology, deep learning has made revolutionary progress in many fields such as computer vision, natural language processing and so on. Using deep learning method to improve the wavefront sensor in adaptive optics system  to achieve more accurate wavefront detection and adapt to more complex application scenarios is the development trend of adaptive optics, and also a new topic in the field of deep learning. This paper, introduces the application status of deep learning in adaptive optics wavefront sensing in detail. It  also analyzes the research characteristics of different types of wavefront sensors, such as phase retrieval wavefront sensor and Shack-Hartmann wavefront sensor, and makes a summary at the end.
基于深度学习的自适应光学波前传感技术综述
波前传感是自适应光学系统的重要组成部分,在地面望远镜、大气激光传输、无线光通信、激光核聚变、自由曲面光学测量等领域发挥着关键作用。同时,作为一项通用的先进技术,深度学习在计算机视觉、自然语言处理等诸多领域都取得了革命性的进展。利用深度学习方法改进自适应光学系统中的波前传感器,实现更精确的波前检测,适应更复杂的应用场景,是自适应光学的发展趋势,也是深度学习领域的一个新课题。本文详细介绍了深度学习在自适应光学波前传感中的应用现状。最后分析了相位恢复波前传感器和Shack-Hartmann波前传感器等不同类型波前传感器的研究特点,并进行了总结。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
强激光与粒子束
强激光与粒子束 Engineering-Electrical and Electronic Engineering
CiteScore
0.90
自引率
0.00%
发文量
11289
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