An Improved Method of Measuring Wavefront Aberration Based on Image with Machine Learning in Free Space Optical Communication.

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ID: 23265
2019
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Abstract
In this paper, an improved method of measuring wavefront aberration based on image with machine learning is proposed. This method had better real-time performance and higher estimation accuracy in free space optical communication in cases of strong atmospheric turbulence. We demonstrated that the network we optimized could use the point spread functions (PSFs) at a defocused plane to calculate the corresponding Zernike coefficients accurately. The computation time of the network was about 6-7 ms and the root-mean-square (RMS) wavefront error (WFE) between reconstruction and input was, on average, within 0.1263 waves in the situation of D/r0 = 20 in simulation, where D was the telescope diameter and r0 was the atmospheric coherent length. Adequate simulations and experiments were carried out to indicate the effectiveness and accuracy of the proposed method.
Reference Key
xu2019ansensors Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Xu, Yangjie;He, Dong;Wang, Qiang;Guo, Hongyang;Li, Qing;Xie, Zongliang;Huang, Yongmei;
Journal sensors
Year 2019
DOI
E3665
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Keywords Keywords not found

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