Airborne LiDAR bathymetry (ALB) system is an attractive and efficient method for nearshore bathymetry and underwater topography mapping. To ensure and improve the measurement accuracy and reliability in various water environments, different receivers using a segmented field of view (FOV) have been designed and are implemented in ALB. These are used to obtain various echo data of multiple channels and perform bathymetry at various water depths. However, in echo waveform processing, detailed information about the water body described by the different echo waveforms is lacking, making it difficult to overcome severe waveform superposition in extremely shallow areas or to separate the weak echo of the water bottom from the noise in extremely deep areas. Therefore, we employed a novel method of multi-channel waveform fusion bathymetry (MWFB) to achieve information complementarity, gain multi-channel waveforms, and detect the robustness of water and bottom echo signals. This method uses an adaptive signal waveform extraction of a multichannel fusion mechanism to eliminate systematic and random noise, and the waveform curvature is used to reconstruct the energy–waveform curves. Iterative decomposition based on waveform curvature and energy curves was conducted to improve the correctness of waveform decomposition and the reliability of waveform components. Furthermore, the water surface and bottom peaks were detected based on the multichannel waveform curvature, which enabled acquisition of the accurate temporal positions of the peaks and achieve high-accuracy bathymetry. According to the experimental results and a comparison with reference datasets, the highest bathymetric accuracy of the MWFB method reached an RMSE of 0.22. For the different study areas, the bathymetric accuracy of the slope reached 95%, 92%, and 97% at Ganquan Island, Lingyang Reef, and Bei Island, respectively. Furthermore, the bathymetric point numbers were effectively increased and bathymetric accuracy was also improved in shallow and deep water, which illustrates the superior bathymetric performance of the MWFB method and its ability to provide a high-efficiency waveform dataset through multi-channel data fusion. The novel LiDAR bathymetric method proposed in this study can effectively achieve high-accuracy nearshore bathymetry and seafloor topographical mapping.

中文翻译：

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测深激光雷达系统多通道波形曲率高精度融合测深

机载激光雷达测深 (ALB) 系统是近岸测深和水下地形测绘的一种有吸引力且高效的方法。为了确保和提高各种水环境中的测量精度和可靠性，使用分段视场（FOV）的不同接收器被设计并在ALB中实现。这些用于获取多个通道的各种回波数据并在各种水深下进行测深。然而，在回波波形处理中，缺乏不同回波波形所描述的水体的详细信息，难以克服极浅区域严重的波形叠加或极深区域的水底微弱回波与噪声的分离。地区。因此，我们采用了一种新的多通道波形融合测深（MWFB）方法来实现信息互补，获得多通道波形，并检测水和海底回波信号的鲁棒性。该方法利用多通道融合机制的自适应信号波形提取来消除系统和随机噪声，并利用波形曲率来重建能量波形曲线。基于波形曲率和能量曲线进行迭代分解，提高波形分解的正确性和波形成分的可靠性。此外，基于多通道波形曲率检测水面和底部峰值，能够获取精确的峰值时间位置，实现高精度测深。根据实验结果以及与参考数据集的比较，MWFB方法的最高测深精度达到RMSE为0.22。不同研究区的甘泉岛、陵阳礁和北岛坡度测深精度分别达到95%、92%和97%。此外，浅水和深水的测深点数得到有效增加，测深精度也得到提高，这说明MWFB方法具有优越的测深性能，能够通过多通道数据融合提供高效的波形数据集。本研究提出的新型激光测深方法可以有效实现高精度近岸测深和海底地形测绘。