Abstract
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).
Highlights
Airborne LiDAR bathymetry offers low cost and high mobility, making it an ideal option for shallowwater measurements
The signal-to-noise ratio (SNR) is a parameter that reflects the intensity of noise on the signal
It is expressed as SNR = 10log Ps, Pv where Ps is the average power of the noise-free signal, and Pv is the average power of the noise
Summary
Airborne LiDAR bathymetry offers low cost and high mobility, making it an ideal option for shallowwater measurements. Airborne LiDAR bathymetry (ALB) is an active remote-sensing technology that plays an important role in shallow-water topographic surveys and measurements. It boasts advantages of low operating cost, strong maneuverability, and high measurement accuracy, and is widely applied to update coastal topographic maps, for coastal construction, to monitor shallow waters, and in other fields[1,2,3]. ALB emits blue and green laser beams and receives signals reflected off various targets. He proposes that full-wave laser data are more conducive to extracting the target position and for research on backscattering from water bodies[3,11]. Target-detection method: Depending on the original waveform, the target-detection method extracts the reflected laser energy time point by identifying the mutation point of the continuous signal reflection energy
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