基于点云过滤的激光雷达云层和气溶胶层探测方法

IF 3.2 2区 物理与天体物理 Q2 OPTICS Optics express Pub Date : 2024-07-29 DOI:10.1364/oe.536588
Xue Shen, Wei Kong, Rujia Ma, Tao Chen, Ye Liu, Genghua Huang, Rong Shu
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引用次数: 0

摘要

本文介绍了一种点云滤波方法,用于从激光雷达数据中检测大气层。该方法涉及基于小波变换函数的上升边缘事件识别。然后根据云层和气溶胶层的连续分布特征,利用基于密度的聚类从原始噪声点云中分离出真实边界。我们利用带噪声的合成激光雷达信号进行了测试,以验证算法的性能。对于信噪比大于 3 的信号,层基检测误差在 ± 5 bins 以内。即使信噪比高于 1,用我们的方法和目测分析得出的结果仍然具有很高的一致性。这些结果表明,我们的算法适用于 CALIOP 等大型时间序列数据集的无监督检测。
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Lidar cloud and aerosol layer detection method based on point cloud filtering
A point cloud filtering method is presented for atmospheric layer detection from lidar data. The method involves rising edge event recognition based on a wavelet transform function. Density-based clustering was then utilized to separate the real boundary from the original noisy point clouds based on continuous distribution characteristics of cloud and aerosol layer. Tests were carried out to verify the performance of our algorithm with synthetic lidar signals with noise. The layer base detection error within ± 5 bins was achieved for signals with SNRs higher than 3. Even for SNRs higher than 1, high consistency was still observed between retrieved results with our method and a visual analysis. These results indicate that our algorithm is suitable for unsupervised detection with large time-series datasets, such as CALIOP.
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来源期刊
Optics express
Optics express 物理-光学
CiteScore
6.60
自引率
15.80%
发文量
5182
审稿时长
2.1 months
期刊介绍: Optics Express is the all-electronic, open access journal for optics providing rapid publication for peer-reviewed articles that emphasize scientific and technology innovations in all aspects of optics and photonics.
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