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A method of measuring wavefront aberration with CNN
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Paper Abstract

Wavefront aberration, which caused by atmospheric turbulence, needs to be measured in the free space optical communication. The existing sensors of wavefront aberration measurement are mainly divided into two classes, wavefront sensors and image-based sensors. Wavefront sensors , such as Hartmann sensor and shearing interferometry, measure wavefront slope to calculate wavefront aberration. However, wavefront sensors always need most of the laser energy, which means it is hard to use wavefront sensors in free space optical communication in the daytime. Image-based sensors usually requires iteration, which means poor real-time and locally optimal solution. No existing method can measure wavefront aberrations in real time in free space optical communication in the daytime. In this article, a new method of measuring wavefront aberration with CNN is proposed, which can be used in free space optical communication in the daytime and have good real-time performance. We made some modifications in VGG to make it can be used to fitting the Zernike coefficients. The input to the network was the PSF of focal plane and defocus plane and the output was the initial estimate of the Zernike coefficients. 22000 pairs of images were collected in the experiment, which produced by liquid crystal and the wavefront was built by 64 Zernike coefficients when atmospheric coherent length(r0) is 5cm. 20000 pairs of images were used as training sets and the other were used as testing sets. The root-mean-square(RMS) wavefront errors of VGG is on average within 0.0487 waves and the time it needs is 11-12ms. We use RMS wavefront error less than 0.1 waves as the correct standard and the correct rate is 98.75% , while other RMS wavefront errors were properly close to 0.1 waves.

Paper Details

Date Published: 18 December 2019
PDF: 6 pages
Proc. SPIE 11342, AOPC 2019: AI in Optics and Photonics, 1134204 (18 December 2019); doi: 10.1117/12.2541544
Show Author Affiliations
Yangjie Xu, Institute of Optics and Electronics (China)
Key Lab. of Optical Engineering (China)
Univ. of Chinese Academy of Sciences (China)
Hongyang Guo, Institute of Optics and Electronics (China)
Key Lab. of Optical Engineering (China)
Univ. of Chinese Academy of Sciences (China)
Qiang Wang, Institute of Optics and Electronics (China)
Key Lab. of Optical Engineering (China)
Univ. of Chinese Academy of Sciences (China)
Dong He, Institute of Optics and Electronics (China)
Key Lab. of Optical Engineering (China)
Univ. of Chinese Academy of Sciences (China)
Yongmei Huang, Institute of Optics and Electronics (China)
Key Lab. of Optical Engineering (China)
Univ. of Chinese Academy of Sciences (China)


Published in SPIE Proceedings Vol. 11342:
AOPC 2019: AI in Optics and Photonics
John Greivenkamp; Jun Tanida; Yadong Jiang; HaiMei Gong; Jin Lu; Dong Liu, Editor(s)

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