Acta Optica Sinica, Volume. 42, Issue 24, 2428003(2022)

Cloud Detection Algorithm of Micro-Pulse Lidar Based on Bidirectional Reconstruction of Backscatter Signal

Yuanyuan Meng1, Jianhua Chang1,2、*, Sicheng Chen1, Mei Zhou1, Tengfei Dai1,2, Boye Wang1, and Yansong Jiang1
Author Affiliations
  • 1School of Electronics & Information Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, Jiangsu , China
  • 2Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing 210044, Jiangsu , China
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    Figures & Tables(16)
    Misjudged isolated clouds
    Comparison of different backscatter signals. (a) Simulated cloud-free signal under uniform atmospheric extinction; (b) normalizd relative backscatter signal without range correction; (c) normalizd relative backscatter signal with range correction; (d) logarithmic-corrected backscatter signal
    Flow chart of cloud detection algorithm of backscatter signal based on bidirectional reconstruction
    Forward reconstruction of backscatter signal. (a) Screening results of forward interpolation points; (b) BA1 obtained by forward interpolation points
    Definition of candidate cloud peak interval. (a) Cloud peaks screened by adaptive threshold; (b) range of candidate cloud peak determined by left and right typical points
    Back reconstruction of backscatter signal. (a) Screening results of back interpolation points; (b) BA2 obtained by back interpolation points
    Cloud layer information retrieved by BA and BLN. (a) Comparison between BA and BLN; (b) inversion result of first-layer cloud; (c) inversion result of second-layer cloud; (d) inversion result of third-layer cloud
    Comparison of different cloud top definitions
    Spatiotemporal distribution of preprocessed backscattering signals
    Detection result of cloud value-added product from SGP station
    Comparison of cloud layer detection results obtained by different algorithms. (a) IDZC; (b) VDE ;(c) SMS-SF ; (d) BRBS
    Comparison of cloud base height inversion performance of different algorithms from 00:00 to 24:00 on January 3, 2020. (a) IDZC; (b) VDE ;(c) SMS-SF; (d) BRBS
    Comparison of cloud top height inversion performance of different algorithms from 00:00 to 24:00 on January 3, 2020. (a) IDZC; (b) VDE ;(c) SMS-SF; (d) BRBS
    Error analysis of different algorithms for data inversion results of SGP station in 2020
    • Table 1. Cloud layer information inversed by different algorithms and their errors with SGP station results

      View table

      Table 1. Cloud layer information inversed by different algorithms and their errors with SGP station results

      AlgorithmCloud layer No.Base height /kmError /kmTop height /kmError /km
      IDZC13.44+0.093.80-0.24
      27.04-0.067.73-0.27
      39.95+0.0610.70-0.24
      VDE13.56+0.213.83-0.21
      27.19+0.097.70-0.30
      3
      SMS-SF13.50+0.153.77-0.27
      27.01-0.097.73-0.27
      39.95+0.1610.91-0.03
      BRBS13.26-0.093.83-0.21
      27.04-0.067.79-0.21
      39.89010.940
    • Table 2. Correlation coefficient and root-mean-square error obtained by different algorithms

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      Table 2. Correlation coefficient and root-mean-square error obtained by different algorithms

      Algorithm

      R of cloud

      base height

      ERMS of cloud base

      height /m

      R of cloud

      top height

      ERMS of cloud top

      height /m

      IDZC0.8647221.30.8334528.9
      VDE0.9464177.40.8850455.9
      SMS-SF0.977457.70.8904327.4
      BRBS0.983643.80.9334280.2
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    Yuanyuan Meng, Jianhua Chang, Sicheng Chen, Mei Zhou, Tengfei Dai, Boye Wang, Yansong Jiang. Cloud Detection Algorithm of Micro-Pulse Lidar Based on Bidirectional Reconstruction of Backscatter Signal[J]. Acta Optica Sinica, 2022, 42(24): 2428003

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    Paper Information

    Category: Remote Sensing and Sensors

    Received: Feb. 24, 2022

    Accepted: May. 18, 2022

    Published Online: Dec. 14, 2022

    The Author Email: Chang Jianhua (jianhuachang@nuist.edu.cn)

    DOI:10.3788/AOS202242.2428003

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