Waveform Processing Methods in Domestic Airborne Lidar Bathymetry System

Tiancheng, 黄田程 Huang; Bangyi, 陶邦一 Tao; Yan, 贺岩 He; Shanjiang, 胡善江 Hu; Jiayong, 俞家勇 Yu; Qiang, 李强 Li; Yunfeng, 朱云峰 Zhu; Guoqing, 尹国清 Yin; Haiqing, 黄海清 Huang; Qiankun, 朱乾坤 Zhu; Fang, 龚芳 Gong

doi:10.3788/lop55.082808

Cited by 2 publications

(1 citation statement)

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“…Airborne LiDAR Bathymetry (ALB) is a remote sensing measurement technology that has developed in recent years [1][2]. Due to its advantages such as wide operation area, high measurement efficiency, low cost, and simultaneous land-sea measurements, it has become a hot topic in research of shallow water areas like nearshore and tidal zones [3][4].…”

Section: Introductionmentioning

confidence: 99%

An effective method for filtering laser bathymetry echo signals

Liu,

Li,

Liu

et al. 2024

International Conference on Signal Processing and Communication Security (ICSPCS 2024)

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Effective echo signal filtering is a waveform preprocessing step in airborne laser bathymetry. To address the low automation in effective echo filtering, we proposed an echo signal filtering method based on the K-means clustering algorithm. First, bathymetry signals were captured and saved as coarse signals using Matlab software. Subsequently, features such as maximum intensity, location of maximum intensity, and half-peak width were extracted from the coarse signals. Finally, K-means clustering algorithm was used to classify the samples, filtering out noise and abnormal pulse signals. The results show that K-means clustering is feasible for signal filtering, with noise signals filtering accuracy of 99% and abnormal pulse signals filtering accuracy of 95%, achieving standards comparable to manual filtering and significantly improving filtering efficiency. This method can further serve as a method for exploring preprocessing of a large amount of bathymetry signals.

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Section: Introductionmentioning

confidence: 99%