Laser & Optoelectronics Progress, Volume. 61, Issue 21, 2101001(2024)

Method for Generating Atmospheric Turbulence Phase Screen Based on Deep Convolutional Generative-Adversarial Networks

Zeyang Wang1,2, Yue Zhu3, and Yan An1,2、*
Author Affiliations
  • 1School of Optoelectronic Engineering, Changchun University of Science and Technology, Changchun 130022, Jilin , China
  • 2Institute of Space Optoelectronics Technology, Changchun University of Science and Technology, Changchun 130022, Jilin , China
  • 3College of Exploration and Geomatics Engineering, Changchun Institute of Technology, Changchun 130021, Jilin , China
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    References(29)

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    [9] Cong M H. Time correlation analysis of laser beam atmospheric transmission phase screen simulation[D](2020).

    [12] Bi C C, Qing C, Qian X M et al. Estimation of atmospheric optical turbulence profile based on back propagation neural network[J]. Laser & Optoelectronics Progress, 58, 2101001(2021).

    [13] Su C D. Optical turbulence forecasting and turbulence degraded image restoration based on machine learning[D](2022).

    [15] Wei D M, Du Q, Liu F N et al. Fractional vortex beam modes recognition based on I-ResNet network[J]. Acta Optica Sinica, 43, 2326001(2023).

    [16] Liu J, Du Q, Liu F N et al. Vortex beam phase correction based on deep phase estimation network[J]. Acta Optica Sinica, 43, 0601013(2023).

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    Zeyang Wang, Yue Zhu, Yan An. Method for Generating Atmospheric Turbulence Phase Screen Based on Deep Convolutional Generative-Adversarial Networks[J]. Laser & Optoelectronics Progress, 2024, 61(21): 2101001

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    Paper Information

    Category: Atmospheric Optics and Oceanic Optics

    Received: Dec. 24, 2023

    Accepted: Feb. 27, 2024

    Published Online: Nov. 18, 2024

    The Author Email: Yan An (anyan_7@126.com)

    DOI:10.3788/LOP232738

    CSTR:32186.14.LOP232738

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