Chinese Journal of Lasers, Volume. 46, Issue 10, 1010001(2019)

Method for Solving Echo Time of Pulse Laser Ranging Based on Deep Learning

Shanjiang Hu1,2, Yan He1, Jiayong Yu3, Deliang Lü4, Chunhe Hou1, and Weibiao Chen1、*
Author Affiliations
  • 1Key Laboratory of Space Laser Communication and Detection Technology, Shanghai Institute of Fine Mechanics and Optics, Chinese Academy of Sciences, Shanghai 201800, China
  • 2University of Chinese Academy of Sciences, Beijing 100049, China
  • 3Shandong University of Science and Technology, Qingdao, Shandong 266590, China
  • 4Hangzhou Tianwei Technology Co., Ltd., Hangzhou, Zhejiang 310026, China
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    References(19)

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    [12] Velas M, Spanel M, Hradis M et al. CNN for very fast ground segmentation in velodyne LiDAR data. [C]∥2018 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC), April 25-27, 2018, Torres Vedras, Portugal. New York: IEEE, 17822925(2018).

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    [14] Dewan A, Oliveira G L, Burgard W. Deep semantic classification for 3D LiDAR data. [C]∥2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September 24-28, 2017, Vancouver, BC, Canada. New York: IEEE, 3544-3549(2017).

    [18] Dai W, Dai C A, Qu S H et al. Very deep convolutional neural networks for raw waveforms. [C]∥2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), March 5-9, 2017, New Orleans, LA, USA. New York: IEEE, 421-425(2017).

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    Shanjiang Hu, Yan He, Jiayong Yu, Deliang Lü, Chunhe Hou, Weibiao Chen. Method for Solving Echo Time of Pulse Laser Ranging Based on Deep Learning[J]. Chinese Journal of Lasers, 2019, 46(10): 1010001

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    Paper Information

    Category: remote sensing and sensor

    Received: Apr. 3, 2019

    Accepted: May. 21, 2019

    Published Online: Oct. 25, 2019

    The Author Email: Chen Weibiao (wbchen@mail.shcnc.ac.cn)

    DOI:10.3788/CJL201946.1010001

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