An interpretation of underwater LiDAR waveforms based on a modified Weibull probability distribution function

Martin A. Montes, A. Vuorenkoski, F. Dalgleish
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引用次数: 3

Abstract

One important research topic in marine optics and active remote sensing is the study of spatial distribution of inherent optical properties (IOPs) in 3-D and at very small scales (i.e., ten to hundredth of mm). The understanding of micro-patchiness has many useful implications in ecology [1], ocean color inversion based on satellite and airborne platforms [2], and improvement of underwater image processing [3]. Here a Fine Structure Underwater Imaging LiDAR (LIght Detection and Range) system (FSUIL) [4] was evaluated for investigating spatial and temporal heterogeneity of water optical components. Each impulse function measured by FSUIL is influenced by the source-detector configuration and by the signal attenuation due to changes on inherent optical properties (IOPs). Thus, for a fixed LiDAR system geometry and a complete characterization of the PMT response, IOPs may be retrieved from FSUIL waveforms. For this task, each raw waveform was simulated based on four shape parameters (i.e., slope, scale, amplitude, and noise baseline, hereafter P1, P2, P3 and P4, respectively) derived from a modified Weibull probability distribution function (MW). Unlike other empirical models, MW estimates may be influenced by multiple scattering and symmetry of main backscattering peak. By assuming a constant LiDAR system configuration, it is expected that P1 increases (i.e., more symmetrical or less skewed Gaussian shape) as multiple scattering is added to the total signal arriving to the detector. The parameter P2 is linked to the width of the Gaussian function and is expected to increase as P2 increases. The parameter P3 relates to the kurtosis of the probability distribution function and is expected to mainly vary with the contribution of retro-reflected and forward-reflected photons after the first and second collision, respectively. A final parameter extracted from MW simulations is P4, a variable associated to the signal `offset'.
基于修正威布尔概率分布函数的水下激光雷达波形解释
海洋光学和主动遥感的一个重要研究课题是研究三维和非常小尺度(即十分之一毫米)的固有光学特性(IOPs)的空间分布。对微斑块的理解在生态学[1]、基于卫星和机载平台的海洋颜色反演[2]以及水下图像处理的改进[3]等方面具有许多有用的意义。本文对一种精细结构水下成像激光雷达(光探测和距离)系统(FSUIL)[4]进行了评估,用于研究水光学成分的时空异质性。FSUIL测量的每个脉冲函数都受到源探测器配置和固有光学特性(IOPs)变化引起的信号衰减的影响。因此,对于固定的LiDAR系统几何形状和PMT响应的完整特征,可以从FSUIL波形中检索IOPs。在本任务中,基于修正威布尔概率分布函数(MW)得出的四个形状参数(即斜率、尺度、幅度和噪声基线,分别为P1、P2、P3和P4)对每个原始波形进行模拟。与其他经验模型不同,谱线估计可能受到多次散射和主后向散射峰对称性的影响。通过假设恒定的LiDAR系统配置,当到达探测器的总信号中加入多重散射时,预计P1会增加(即更对称或更少偏斜的高斯形状)。参数P2与高斯函数的宽度相关联,并随着P2的增加而增加。参数P3与概率分布函数的峰度有关,预计主要随第一次和第二次碰撞后反向反射和正向反射光子的贡献而变化。从MW模拟中提取的最后一个参数是P4,一个与信号“偏移”相关的变量。
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