• Journal of Infrared and Millimeter Waves
  • Vol. 39, Issue 4, 483 (2020)
Wen-Hao ZHANG, Song LI*, Yue MA, Zhi-Yu ZHANG, and Pu-Fan Zhao
Author Affiliations
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    DOI: 10.11972/j.issn.1001-9014.2020.04.013 Cite this Article
    Wen-Hao ZHANG, Song LI, Yue MA, Zhi-Yu ZHANG, Pu-Fan Zhao. Photon-counting lidar simulation method based on three-dimensional sea surface[J]. Journal of Infrared and Millimeter Waves, 2020, 39(4): 483 Copy Citation Text show less
    Geometry of laser reflection on a facet of the sea surface
    Fig. 1. Geometry of laser reflection on a facet of the sea surface
    The process of generating photon distribution based on the Monte Carlo method
    Fig. 2. The process of generating photon distribution based on the Monte Carlo method
    Simulation process of photon-counting lidar on sea surface targets(a) spatial distribution of sea surface heights, (b) spatial distribution of normalized energy, (c) spatial distribution of BRDF at different locations,(d) number of signal photons returned from different locations
    Fig. 3. Simulation process of photon-counting lidar on sea surface targets(a) spatial distribution of sea surface heights, (b) spatial distribution of normalized energy, (c) spatial distribution of BRDF at different locations,(d) number of signal photons returned from different locations
    Photon point cloud distribution generated based on random sea surface simulation (a) distribution of returning photons, (b) cumulative histogram of simulated photons
    Fig. 4. Photon point cloud distribution generated based on random sea surface simulation (a) distribution of returning photons, (b) cumulative histogram of simulated photons
    ATLAS's photon distribution in the verification region of East Pacific
    Fig. 5. ATLAS's photon distribution in the verification region of East Pacific
    Relationship between the average number of photons per single-pulse and the wind speed above sea surface
    Fig. 6. Relationship between the average number of photons per single-pulse and the wind speed above sea surface
    Elevation biases and standard deviations for photon-counting lidars at different wind speeds (a)averaged elevation bias, (b) elevation standard deviation
    Fig. 8. Elevation biases and standard deviations for photon-counting lidars at different wind speeds (a)averaged elevation bias, (b) elevation standard deviation
    参数符号数值参数符号数值
    探测效率Pq0.15波长λ532 nm
    发射效率ηt0.504接收系统面积Ar0.50 m2
    接收效率ηr0.4轨道高度Hz500 km
    光束发散角(1/e2)θat35 µrad死区时间τt3.2 ns
    脉冲能量Et160 µJ大气透过率T00.9
    Table 1. 仿真使用的ATLAS系统参数和环境参数[20-21]

    风速

    /(m/s)

    统计信号光子数

    /counts

    仿真信号光子数

    /counts

    相对误差

    /(%)

    24.14.10
    33.93.3-15.4
    43.22.8-12.5
    52.72.4-11.1
    62.32.1-8.7
    72.11.9-9.5
    81.81.7-5.6
    91.51.66.7
    101.41.40
    111.31.30
    Table 2. 星载光子计数激光雷达的海面目标仿真点云与ATLAS实测点云的统计对比
    Wen-Hao ZHANG, Song LI, Yue MA, Zhi-Yu ZHANG, Pu-Fan Zhao. Photon-counting lidar simulation method based on three-dimensional sea surface[J]. Journal of Infrared and Millimeter Waves, 2020, 39(4): 483
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