Large-scale piston error detection technology for segmented optical mirrors via convolutional neural networks

doi:10.1364/ol.44.001170

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	Large-scale piston error detection technology for segmented optical mirrors via convolutional neural networks
	D.Q.Li; S.Y.Xu; D.Wang; D.J.Yan
	2019
发表期刊	Optics Letters
ISSN	0146-9592
卷号	44 期号:5 页码:1170-1173
摘要	In the cophasing of the segmented opticalmirrors, the Shack-Hartmann wavefront sensor is not sensitive to the submirror piston error and the large range piston errors beyond the cophasing detection range of phase diversity algorithm. It is necessary to introduce specific sensors (e.g., microlenses or prisms), but they greatly increase the complexity and manufacturing cost of the optical system. In this Letter, we introduce the convolutional neural network (CNN) to distinguish the piston error range of each submirror. To get rid of the dependence of the CNN dataset on the imaging target, we construct the feature vector by the in-focal and defocused images. The method surpasses the fundamental limit of the detection range by using different wavelengths. Finally, the results of the simulation experiment indicate that the method is effective. (c) 2019 Optical Society of America
关键词	Optics
DOI	10.1364/ol.44.001170
URL	查看原文
收录类别	SCI ; EI
语种	英语
引用统计
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/63273
专题	中国科学院长春光学精密机械与物理研究所
推荐引用方式 GB/T 7714	D.Q.Li,S.Y.Xu,D.Wang,et al. Large-scale piston error detection technology for segmented optical mirrors via convolutional neural networks[J]. Optics Letters,2019,44(5):1170-1173.
APA	D.Q.Li,S.Y.Xu,D.Wang,&D.J.Yan.(2019).Large-scale piston error detection technology for segmented optical mirrors via convolutional neural networks.Optics Letters,44(5),1170-1173.
MLA	D.Q.Li,et al."Large-scale piston error detection technology for segmented optical mirrors via convolutional neural networks".Optics Letters 44.5(2019):1170-1173.

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