A Deep Learning Method for LiDAR Bathymetry Waveforms Processing

The shallow water areas, such as near shore, near reef, shallow sea and wetland, are blind areas for detection, and are also important research fields of LiDAR bathymetry technology. In this paper, we used the self-developed LiDAR bathymetry experimental system to obtain echo waveforms in the air and water tank in the laboratory. A deep learning method of one-dimensional convolutional neural network was proposed to directly invert the depth of water based on these original experimental echo data. The results denote that the deep learning method is feasible for the processing of large amount of LiDAR bathymetry echo waveforms. This method can be further used for echo waveforms processing outdoor.