Waveform decompostion of lidar pulse based on the variable component parameter random sampling method
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摘要: 激光雷达脉冲回波的波形分解方法是提取其波形参数的重要手段，也为反演目标高度、倾斜度和粗糙度、反射率提供直接的参数来源。针对部分信噪比较差且具有一定混叠程度的脉冲回波，提出一种基于可变分量的参数随机抽样方法的波形分解算法（WDVCM）。该算法以高斯混合函数为优化模型，通过随机产生高斯分量的特征参数以及删减或生成高斯分量等操作，并分别基于能量函数和拟合标准差作为参数优化的判据，从而实现波形的分解及其参数提取。利用该算法对美国国家航空航天局（NASA）的对地观测星载激光雷达（GLAS）一个条带中的4584个原始波形进行了处理分析。结果发现，约99%的WDVCM和97%的NASA拟合波形结果的相关系数均超过0.95，其中两者相关系数差异不超过0.05占98%。同时，WDVCM和NASA拟合波形的标准差系数均值分别为2.21和3.28，约89%的WDVCM拟合波形的标准差系数均小于NASA拟合波形的标准差系数。所得结果表明，WDVCM对混叠高斯波形的拟合效果更好，适用性更强。Abstract: The waveform decomposition method of Lidar pulse signal is an important way to extract the waveform parameters, which provides significant data sources for retrieving the elevation, slope, roughness and reflectance of target. A waveform decomposition algorithm on variable component parameter random sampling method (WDVCM) was proposed to process waveforms with poor SNR and certain overlapping. The algorithm regarded the compounded Gaussian function as the optimization model, and achieved the decomposition and extraction of raw waveforms by generating randomly characteristic parameters and deleting or creating Gaussian component, based on the energy function and the standard deviation of fitting as the criterion for parameter optimization. About 4584 raw waveforms in a stripe of Geoscience Laser Altimeter System (GLAS) developed by National Aeronautics and Space Administration (NASA) were processed using the WDVCM. The result indicates that proportions of fitting waveforms originated from WDVCM and NASA with correlation coefficient over 0.95 are 99% and 97% respectively. Wherein, the ratio with the differences of correlation coefficient less than 0.05 is about 98%. The averages of standard deviation coefficient (SDC) of fitting waveforms provided by WDVCM and the NASA are 2.21 and 3.28, and about 89% of SDC of fitting waveforms processed by WDVCM is less than that from NASA. It proves that the WDVCM is more applicable for decomposing overlapping waveforms with better fitting effect.
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[1] Park T, Kennedy R E, Choi S, et al. Application of physically-based slope correction for maximum forest canopy height estimation using waveform LiDAR across different footprint sizes and locations:Tests on LVIS and GLAS[J]. Remote Sensing, 2014, 6(7):6566-6586. [2] Allouis T, Durrieu S, Couteron P. A new method for incorporating hillslope effects to improve canopy-height estimates from large-footprint LIDAR waveforms[J]. IEEE Geoscience Remote Sensing Letters, 2012, 9(4):730-734. [3] Clment Mallet, Frdric Bretar, Roux M, et al. Relevance assessment of full-Waveform lidar data for urban area classification[J]. ISPRS Journal of Photogrammetry Remote Sensing, 2011, 66(6):S71-S84. [4] Hofton M A, Minster J B, Blair J B. Decomposition of laser altimeter waveforms[J]. IEEE Transactions on Geoscience and Remote Sensing, 2000, 38(4):1989-1996. [5] Li Q. Decomposition of airborne laser scanning waveform data based on EM algorithm[J]. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2008, 37(PART B1):211-218. [6] Hong-Chao M A. Modified EM algorithm and its application to the decomposition of laser scanning waveform data[J]. Journal of Remote Sensing, 2009, 13(1):35-41. [7] Jung J, Crawford M M. A two-stage approach for decomposition of ICESat waveforms[C]//IEEE International Geoscience Remote Sensing Symposium. IEEE, 2009. [8] Slobbe D C, Lindenebergh. Estimation of volume change rates of Greenland's ice sheet from ICESat data using overlapping footprints[J]. Remote Sensing of Environment, 2008, 112(12):4204-4213. [9] Mallet C, ment, Lafarge F. A marked point process for modeling lidar waveforms[J]. IEEE Trans Image Process, 2010, 19(12):3204-3221. [10] Zhao Quanhua, Li Hongying, Li Yu. Gaussian mixture model with variable components for full waveform LiDAR data decomposition and RJMCMC algorithm[J]. Acta Geodaetica et Cartographica Sinica, 2015, 44(12):1367-1377. (in Chinese)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[J]. 测绘学报, 2015, 44(12):1367-1377. [11] Mallet C, Lafarge F, Roux M, et al. A marked point process for modeling lidar waveforms[J]. IEEE Transactions on Image Processing A Publication of the IEEE Signal Processing Society, 2010, 19(12):3204-3221. [12] Gardner C S. Ranging performance of satellite laser altimeters[J]. IEEE Transactions on Geoscience Remote Sensing, 1992, 30(5):1061-1072. [13] Harding D J, Bufton J L, Frawley J J. Satellite laser altimetry of terrestrial topography:vertical accuracy as a function of surface slope, roughness, and cloud cover[J]. IEEE Transactions on Geoscience and Remote Sensing, 1994, 32(2):329-339. -
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