大光斑LiDAR全波形数据小波变换的高斯递进分解
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摘要
高斯分解是波形激光雷达数据预处理的常用方法,但在应用于大光斑全波形激光雷达数据中的叠加波时却难以发挥作用,为此提出一种基于小波变换的高斯递进波形分解方法.首先,利用小波变换多尺度分析特性检测出目标地物并准确估算组分特征参数,进而建立高斯模型优化特征参数;然后通过拟合精度指标,判断是否需要添加新组分进行逐级递进分解,确定最终模型及其组分构成,最终实现全波形激光雷达数据的波形分解.为了验证算法的有效性,分别对实验数据使用本文算法和常用的基于拐点匹配的高斯分解法进行分析,结果表明,本文算法提取的目标数几乎是拐点匹配算法的2倍,可以有效地从叠加波中检测出目标组分,且拟合精度高于98%.
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%.
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%.
引文
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[10]Ma H C,Li Q.Modified EM algorithm and its application to the decomposition of laser scanning waveform data[J].Journal of Remote Sensing.2009,13(1):35-41.
[11]LAI Xu-Dong,QIN Nan-Nan,HAN Xiao-Shuang,et al.Iterative decomposition method for small foot-print LiDAR waveform[J].Journal of Infrared and Millimeter Waves(赖旭东,秦楠楠,韩晓爽,等.一种迭代的小光斑LiDAR波形分解方法.红外与毫米波学报),2013,32(4):319-324.
[12]QIN Yu-Chu,LI Bin,NIU Zheng,et al.Stepwise decomposition and relative radiometric normalization for small footprint LiDAR waveform[J].Sci China Earth Sci(覃驭楚,李斌,牛铮,等.小光斑激光雷达全波形数据递进分解与相对辐射校正.中国科学:地球科学),2011,41(1):103-109.
[13]ZHAO Quan-Hua,LI Hong-Ying,LI Yu.Gaussian mixture with variable components for full-waveform LiDAR data decomposition and RJMCMC algorithm[J].Acta Geodaetica et Cartographica Sinica(赵泉华,李红莹,李玉.全波形LiDAR数据分解的可变分量高斯混合模型及RJMCMC算法.测绘学报),2015,44(12):1367-1377.
[14]DAI Can,WANG Yuan-Qing,XU Fan.3-D LiDAR echo decomposition based on particle swarm optimization[J].Laser Technology(戴璨,王元庆,徐帆.基于粒子群算法的3维激光雷达回波分解.激光技术),2016,40(2):284-287.
[15]Lin Y C,Mills J P,Smithvoysey S,et al.Rigorous pulse detection from full-waveform airborne laser scanning data[J].International Journal of Remote Sensing.2010,31(5):1303-1324.
[16]WANG Jin-Hu.Full-waveform LiDAR data processing and application technology[D].Beijing:Institute of Remote Sensing Application Chinese Academy of Sciences(王金虎.全波形激光雷达数据处理与应用技术研究.北京:中国科学院遥感应用研究所),2012.
[17]MA Peng-Ge,LIU Yi,QI Lin,et al.Wavelet filter algorithm for echo signal of pulsed LiDAR at low SNR[J].Electronics Optics&Control(马鹏阁,柳毅,齐林,等.低信噪比下脉冲激光雷达回波信号小波域滤波算法.光电与控制),2011,4(04):26-29.
[18]SHAO Xue-Guang,CAI Wen-Sheng,SUN Pei-Yan.Determination of the component number in overlapping multicomponent chromatogram using wavelet transform[J].Chemometrics&Intelligent Laboratory Systems.1998,43(1):147-155.
[19]JIAO Long,GAO Su-Ya,ZHANG Fang,et al.Quantification of components in overlapping peaks from capillary electrophoresis by using continues wavelet transform method[J].Talanta.2008,75(4):1061-1067.
[20]ZHANG De-Feng.Wavelet analysis in Matlab.Second Edition[M].Beijing:China Machine Press(张德丰.MATLAB小波分析.第2版.北京:机械工业出版社),2012.
[21]Wang C,Tang F X,Li L W,et al.Wavelet analysis for ICESat/GLAS waveform decomposition and its application in average tree height estimation[J].IEEE Geoscience&Remote Sensing Letters.2013,10(1):115-119.
[22]Brenner A C,Zwally H J,Bentley C R,et al.Derivation of range and range distributions from laser pulse waveform analysis for surface elevations,roughness,slope,and vegetation heights[J].Algorithm Theoretical Basis Document v4.1,2003.
[23]Madsen K,Nielsen H B,Tingleff O.Methods for nonlinear least squares problems[M].Denmark:Press of Technical University of Denmark,2004.
[2]Lefsky M A,Cohen W B,Harding D J,et al.LiDAR remote sensing of above-ground biomass in three biomes[J].Global Ecology&Biogeography.2002,11(5):393-399.
[3]Gong P,Li Z,Huang H B,et al.ICESat GLAS Data for urban environment monitoring[J].IEEE Transactions on Geoscience&Remote Sensing.2011,49(3):1158-1172.
[4]LI Zhan.3D extraction of urban buildings based on ICESat/GLAS data[D].Beijing:Institute of Remote Sensing Application Chinese Academy of Sciences(李展.基于ICESat GLAS数据提取城市建筑物的三维信息.北京:中国科学院遥感应用研究所),2011.
[5]Sun G Q,Ranson K J.Modeling LiDAR returns from forest canopies[J].Geoscience&Remote Sensing IEEE Transactions on.2000,38(6):2617-2626.
[6]Ni-Meister W,Strahler A H,Woodcock C E,et al.Modeling the hemispherical scanning,below-canopy LiDAR and vegetation structure characteristics with a geometric-optical and radiative-transfer model[J].Canadian Journal of Remote Sensing.2008,34(S2):S385-S397.
[7]Ni-Meister W,Jupp D L B,Dubayah R.Modeling LiDAR waveforms in heterogeneous and discrete canopies[J].IEEE Transactions on Geoscience&Remote Sensing.2001,39(9):1943-1958.
[8]Wagner W,Ullrich A,Ducic V,et al.Gaussian decomposition and calibration of a novel small-footprint full-waveform digitising airborne laser scanner[J].ISPRS Journal of Photogrammetry&Remote Sensing.2006,60(2):100-112.
[9]Chauve A,Mallet C,Bretar F,et al.Processing full-waveform LiDAR data:modelling raw signals[C].International Archives of Photogrammetry,Remote Sensing and Spatial Information Sciences,36(Part 3/W52).2008:102-107.
[10]Ma H C,Li Q.Modified EM algorithm and its application to the decomposition of laser scanning waveform data[J].Journal of Remote Sensing.2009,13(1):35-41.
[11]LAI Xu-Dong,QIN Nan-Nan,HAN Xiao-Shuang,et al.Iterative decomposition method for small foot-print LiDAR waveform[J].Journal of Infrared and Millimeter Waves(赖旭东,秦楠楠,韩晓爽,等.一种迭代的小光斑LiDAR波形分解方法.红外与毫米波学报),2013,32(4):319-324.
[12]QIN Yu-Chu,LI Bin,NIU Zheng,et al.Stepwise decomposition and relative radiometric normalization for small footprint LiDAR waveform[J].Sci China Earth Sci(覃驭楚,李斌,牛铮,等.小光斑激光雷达全波形数据递进分解与相对辐射校正.中国科学:地球科学),2011,41(1):103-109.
[13]ZHAO Quan-Hua,LI Hong-Ying,LI Yu.Gaussian mixture with variable components for full-waveform LiDAR data decomposition and RJMCMC algorithm[J].Acta Geodaetica et Cartographica Sinica(赵泉华,李红莹,李玉.全波形LiDAR数据分解的可变分量高斯混合模型及RJMCMC算法.测绘学报),2015,44(12):1367-1377.
[14]DAI Can,WANG Yuan-Qing,XU Fan.3-D LiDAR echo decomposition based on particle swarm optimization[J].Laser Technology(戴璨,王元庆,徐帆.基于粒子群算法的3维激光雷达回波分解.激光技术),2016,40(2):284-287.
[15]Lin Y C,Mills J P,Smithvoysey S,et al.Rigorous pulse detection from full-waveform airborne laser scanning data[J].International Journal of Remote Sensing.2010,31(5):1303-1324.
[16]WANG Jin-Hu.Full-waveform LiDAR data processing and application technology[D].Beijing:Institute of Remote Sensing Application Chinese Academy of Sciences(王金虎.全波形激光雷达数据处理与应用技术研究.北京:中国科学院遥感应用研究所),2012.
[17]MA Peng-Ge,LIU Yi,QI Lin,et al.Wavelet filter algorithm for echo signal of pulsed LiDAR at low SNR[J].Electronics Optics&Control(马鹏阁,柳毅,齐林,等.低信噪比下脉冲激光雷达回波信号小波域滤波算法.光电与控制),2011,4(04):26-29.
[18]SHAO Xue-Guang,CAI Wen-Sheng,SUN Pei-Yan.Determination of the component number in overlapping multicomponent chromatogram using wavelet transform[J].Chemometrics&Intelligent Laboratory Systems.1998,43(1):147-155.
[19]JIAO Long,GAO Su-Ya,ZHANG Fang,et al.Quantification of components in overlapping peaks from capillary electrophoresis by using continues wavelet transform method[J].Talanta.2008,75(4):1061-1067.
[20]ZHANG De-Feng.Wavelet analysis in Matlab.Second Edition[M].Beijing:China Machine Press(张德丰.MATLAB小波分析.第2版.北京:机械工业出版社),2012.
[21]Wang C,Tang F X,Li L W,et al.Wavelet analysis for ICESat/GLAS waveform decomposition and its application in average tree height estimation[J].IEEE Geoscience&Remote Sensing Letters.2013,10(1):115-119.
[22]Brenner A C,Zwally H J,Bentley C R,et al.Derivation of range and range distributions from laser pulse waveform analysis for surface elevations,roughness,slope,and vegetation heights[J].Algorithm Theoretical Basis Document v4.1,2003.
[23]Madsen K,Nielsen H B,Tingleff O.Methods for nonlinear least squares problems[M].Denmark:Press of Technical University of Denmark,2004.