Ma, Y.; Zhang, J.; Zhang, Z., and Zhang, J.Y., 2019. Bathymetry retrieval method of LiDAR waveform based on multi-Gaussian functions. In: Jung, H.-S.; Lee, S.; Ryu, J.-H., and Cui, T. (eds.), Advances in Remote Sensing and Geoscience Information Systems of Coastal Environments. Journal of Coastal Research, Special Issue No. 90, pp. 324-331. Coconut Creek (Florida), ISSN 0749-0208.
This paper provides a water depth inversion approach to laser radar waveform data based on multi-Gauss function in order to address the following two problems: the impact of noise on the traditional bathymetry and the poor accuracy of the water depth inversion in deep water. This approach employs L-M optimization algorithm to make multiple Gauss functions iterate and fit the LiDAR waveform data, and then uses peak detection method to extract the echo signal from the surface and the bottom of the water. In this paper, the water depth inversion is carried out using the simulation data of LiDAR water echo and the Aquarius LiDAR waveform data around the water area of the Ganquan Island respectively. Taking the mean relative error (MRE) and the mean absolute error (MAE) as the evaluation index of accuracy, the result shows that the detection model of LiDAR bathymetry has a higher ability of water depth inversion in the range of detectable water depth. For simulation data, the MAE is 20 cm and the MRE is below 7 % in the water depth range of 2 m to 10 m. While for real LiDAR waveform data, the MAE of water depth inversion is between 30 cm and 75 cm, and the MRE is below 12 %.