An Assessment of Waveform Processing for a Single-Beam Bathymetric LiDAR System (SBLS-1)

Abstract

The single-beam bathymetric light detection and ranging (LiDAR) system 1 (SBLS-1), which is equipped with a 532-nm-band laser projector and two concentric-circle receivers for shallow- and deep-water echo signals, is a lightweight and convenient prototype instrument with low energy consumption. In this study, a novel LiDAR bathymetric method is utilized to achieve single-beam and dual-channel bathymetric characteristics, and an adaptive extraction method is proposed based on the cumulative standard deviation of the peak and trough, which is mainly used to extract the signal segment and eliminate system and random noise. To adapt the dual-channel bathymetric mechanism, an automatic channel-selection method was used at various water depths. A minimum half-wavelength Gaussian iterative decomposition is proposed to improve the detection accuracy of the surface- and bottom-water waveform components and ensure bathymetric accuracy and reliability. Based on a comparison between the experimental results and in situ data, it was found that the SBLS-1 obtained a bathymetric accuracy and RMSE of 0.27 m and 0.23 m at the Weifang and Qingdao test fields. This indicates that the SBLS-1 was bathymetrically capable of acquiring a reliable, high-efficiency waveform dataset. Hence, the novel LiDAR bathymetric method can effectively achieve high-accuracy near-shore bathymetry.

Improving Shallow Water Bathymetry Inversion through Nonlinear Transformation and Deep Convolutional Neural Networks

“…Various forms of LiDAR, such as full-waveform [4] and photon-counting LiDAR [5], have been developed to address these issues. They make use of advanced statistical filtering methods to accurately identify moments of water surface and bottom reflection [6][7][8]. Despite its successes in applications such as shallow water bathymetry [9] and coastal topography [10], the uneven and sparse distribution of LiDAR data necessitates the use of passive remote sensing methods, such as optical and multispectral remote sensing, to achieve comprehensive bathymetric mapping.…”