Acta Optica Sinica, Volume. 39, Issue 8, 0801002(2019)

Atmospheric Optical Path Airflow Disturbance Analysis Method Based on Convolutional Neural Network

Yichen Liu*, Kan Wu**, Gaofeng Qiu, and Jianping Chen
Author Affiliations
  • State Key Laboratory of Advanced Optical Communication Systems and Networks,Shanghai Jiao Tong University, Shanghai 200240, China
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    A method to investigate optical path turbulence based on laser spot distortion and a convolutional neural network (CNN) is proposed. Utilizing the CNN, we evaluated the spot distortion of laser beams resulting from airflow disturbance in space propagation. As a result, details of turbulence on the beam propagation path can be obtained. Experimental results demonstrate a high correlation between the evaluation parameter and the turbulent intensity (wind speed) measured by an anemoscope. The proposed method provides a turbulence analysis with short distance, high speed, and low cost.

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    Yichen Liu, Kan Wu, Gaofeng Qiu, Jianping Chen. Atmospheric Optical Path Airflow Disturbance Analysis Method Based on Convolutional Neural Network[J]. Acta Optica Sinica, 2019, 39(8): 0801002

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    Paper Information

    Category: Atmospheric Optics and Oceanic Optics

    Received: Mar. 11, 2019

    Accepted: Apr. 15, 2019

    Published Online: Aug. 7, 2019

    The Author Email: Liu Yichen (lycwahaha@sjtu.ed.cn), Wu Kan (kanwu@sjtu.edu.cn)

    DOI:10.3788/AOS201939.0801002

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