Song Yue, Li Houpu, Zhai Guojun, He Yan, Bian Shaofeng, Zhou Wei
Department of Navigation Engineering, Naval University of Engineering, Wuhan, 430033, China.
Naval Institute of Marine Environment, Tianjin, 300061, China.
Sci Rep. 2021 Aug 20;11(1):16988. doi: 10.1038/s41598-021-96551-w.
Airborne LiDAR bathymetry offers low cost and high mobility, making it an ideal option for shallow-water measurements. However, due to differences in the measurement environment and the laser emission channel, the received waveform is difficult to extract using a single algorithm. The choice of a suitable waveform processing method is thus of extreme importance to guarantee the accuracy of the bathymetric retrieval. In this study, we use a wavelet-denoising method to denoise the received waveform and subsequently test four algorithms for denoised-waveform processing, namely, the Richardson-Lucy deconvolution (RLD), blind deconvolution (BD), Wiener filter deconvolution (WFD), and constrained least-squares filter deconvolution (RFD). The simulation and measured multichannel databases are used to evaluate the algorithms, with focus on improving their performance after data-denoising and their capability of extracting water depth. Results show that applying wavelet denoising before deconvolution improves the extraction accuracy. The four algorithms perform better for the shallow-water orthogonal polarization channel (PMT2) than for the shallow horizontal row polarization channel (PMT1). Of the four algorithms, RLD provides the best signal-detection rate, and RFD is the most robust; BD has low computational efficiency, and WFD performs poorly in deep water (< 25 m).
机载激光雷达测深具有低成本和高机动性的特点，使其成为浅水测量的理想选择。然而，由于测量环境和激光发射通道的差异，使用单一算法难以提取接收到的波形。因此，选择合适的波形处理方法对于保证测深反演的准确性至关重要。在本研究中，我们使用小波去噪方法对接收到的波形进行去噪，随后测试四种去噪波形处理算法，即理查森- Lucy反卷积（RLD）、盲反卷积（BD）、维纳滤波器反卷积（WFD）和约束最小二乘滤波器反卷积（RFD）。利用模拟和实测多通道数据库对算法进行评估，重点是提高去噪后算法的性能及其提取水深的能力。结果表明，在反卷积之前应用小波去噪可提高提取精度。四种算法在浅水正交极化通道（PMT2）上的表现优于浅水水平行极化通道（PMT1）。在这四种算法中，RLD的信号检测率最高，RFD最稳健；BD计算效率低，WFD在深水（< 25米）中表现不佳。
