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Assessment of Quadrilateral Fitting of the Water Column Contribution in Lidar Waveforms on Bathymetry Estimates

机译:基于测深估计的激光雷达波形中水柱贡献的四边形拟合评估

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摘要

A new approach based on a mixture of Gaussian and quadrilateral functions was developed to process bathymetric lidar waveforms. The approach was tested on two simulated data sets obtained from the existing Water-LIDAR (Wa-LID) waveform simulator. The first simulated data set corresponds to a sensor configuration modeled after a possible future satellite bathymetric lidar sensor that was previously studied. The second simulated data set corresponds to a lidar airborne configuration modeled using the HawkEye airborne lidar parameters. In the proposed approach, the lidar waveform is fitted into a combination of three functions, two Gaussians for both the water surface and water bottom contributions and a quadrilateral function to fit the water column contribution. The results show more accurate bathymetry estimates compared with the use of a triangular function to fit the column contribution or a simple peak detection method. For the satellite configuration, the bias is improved by 16.8 and 0.8 cm compared with the peak detection method and the use of a triangular function, respectively. For the airborne configuration, the bias is improved by 10.0 and 2.4 cm compared with the peak detection method and the use of a triangular function, respectively. The proposed waveform fitting using the quadrilateral function underestimates the bathymetry by $-$5.0 and $-$ 6.1 cm for the simulated satellite and airborne data sets, respectively. The standard deviations of the bathymetry estimates are 6.0 and 8.2 cm, respectively. The obtained biases are inherent to overlaps between functions fitting the water surface, column, and bottom contributions.
机译:开发了一种基于高斯函数和四边形函数混合的新方法来处理测深激光雷达波形。在从现有的Water-LIDAR(Wa-LID)波形模拟器获得的两个模拟数据集上对该方法进行了测试。第一模拟数据集对应于在先前可能研究的未来卫星测深激光雷达传感器之后建模的传感器配置。第二个模拟数据集对应于使用HawkEye机载激光雷达参数建模的激光雷达机载配置。在提出的方法中,将激光雷达波形拟合为三个函数的组合,两个高斯函数分别用于水面和水底贡献,以及四边形函数以拟合水柱贡献。结果表明,与使用三角函数来拟合色谱柱贡献值或使用简单的峰检测方法相比,测深估算更加准确。对于卫星配置,与峰值检测方法和三角函数相比,偏置分别提高了16.8和0.8 cm。对于机载配置,与峰值检测方法和三角函数相比,偏置分别提高了10.0和2.4 cm。拟议的使用四边形函数的波形拟合将模拟卫星和机载数据集的测深法分别低估了$-$ 5.0和$-$ 6.1 cm。测深法估计的标准偏差分别为6.0和8.2 cm。所获得的偏差是拟合水面,水柱和水底影响的函数之间重叠所固有的。

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