红外与毫米波学报2017，Vol.36Issue(6)：749-755,7.DOI:10.11972/j.issn.1001-9014.2017.06.019
大光斑LiDAR全波形数据小波变换的高斯递进分解
Wavelet transform of Gaussian progressive decomposition method for full-waveform LiDAR data
摘要
Abstract
Gaussian decomposition is a commonly used method for waveform analysis,which is a key post-processing step for the applications of large footprint LiDAR data.However,it usually fails to detect the overlapping pulses of large-footprint waveform data.Therefore,a Gaussian progressive decomposition method based on wavelet transform was proposed in this study to address this issue and applied to Ice,Cloud,and land Elevation Satellite / Geoscience Laser Altimeter System (ICESat/GLAS) data.The new proposed method mainly consists of three key steps.First,the wavelet transform was adopted to detect the target features and estimate the component feature parameters,then the Gaussian model was established to optimize the feature parameters.Second,a new component was added if the fitting accuracy didn't meet the requirements.Finally,waveform decomposition based on wavelet transform was completed until no more new components were added.Additionally,a comparison experiment between the new proposed method and the Gaussian decomposition method based on inflection point was also conducted to verify the reliability of the new proposed algorithm.Experiment results indicated that our new proposed algorithm can detect twice targets as many as the method based on inflection point,and effectively decompose the targets from overlapping waveforms due to high fitting accuracy of above 98 ％.关键词
大光斑激光雷达/全波形分析/小波变换/高斯分解/特征参数Key words
large footprint LiDAR/full-waveform analysis/wavelet transform/Gaussian decomposition/feature parameter分类
天文与地球科学引用本文复制引用
杨学博,王成,习晓环,田建林,聂胜,朱笑笑..大光斑LiDAR全波形数据小波变换的高斯递进分解[J].红外与毫米波学报,2017,36(6):749-755,7.基金项目
国家重点研发计划资助(2017YFA0603002),国家自然科学基金面上项目(41271428) （2017YFA0603002）
Supported by National Key R&D Program of China (2017YFA0603002),and National Natural Science Foundation of China (41271428) （2017YFA0603002）
