基于LM算法的机载LiDAR全波形数据分解研究

Research on Full Waveform Airborne Laser Radar Data Decomposition Based on LM Algorithm

全波形机载激光雷达系统采集的波形数据蕴含着丰富的地物信息,因此,这些地物信息的提取方法具有很大的研究价值。本文通过对全波形数据的去噪平滑以及LM参数优化算法实现了波形分解,并利用其结果生成的点云数据与系统点云数据进行对比,结合部分点云剖面图分析其给实际生产应用所带来的帮助,实验表明,本文所用方法可以有效地提高数据中地物信息的质量。

Full waveform airborne laser radar systems acquired waveform data contains an abundance ofinformation about the feature, so these feature information extraction methods has great research value. In this paper, the waveform data is processed to remove noise and smoothing, then use LM waveform decomposition algorithm. Finally, the experimental generate point cloud data is used to compar- ison with the system point cloud data, then combined with some point cloud profile analysis to the practical application of production and application of the help. The experiments show that the method used herein can effectively improve the quality of data in the feature information.