激光测高仪回波分解算法

开发了一种激光测高仪回波基本信息提取算法，对回波数据进行了高斯波分解，获取了高斯波分量的个数，及每个高斯波分量的波中心位置、宽度和幅度等参数．该算法首先根据回波拐点的数目和位置确定出高斯分量的个数及每个高斯分量的波中心位置和宽度初始值，随后利用线性最小二乘法计算出每个高斯分量的幅度，最后将经过选择和标记的高斯分量针对实际回波采用Levenberg-Marquardt方法进行拟合，得到优化后的高斯波基本参数．通过这些基本参数信息，能够进一步推导出激光测高仪光斑内各个反射表面的垂直分布、起伏程度和反射率等基本信息．

Decomposing Algorithm of Laser Altimeter Waveforms

A method to extract the basic information from laser altimeter return waveforms is de-veloped, by which decompose a laser altimeter return waveform into a series of Gaussian components and obtain the number of the Gaussian components and the position, half-width and amplitude of each Gaussian component. From these basic parameters, the topographic information as the ele-vations and distributions, the surface slope and roughness, and the albedos of distinct reflecting surfaces within the laser footprint can be further induced. Firstly, the initial values of the number of Gaussian components and the position, half-wide of each component are estimated from the num-ber and positions of the waveform's inflection points. Secondly the linear least-squares method are used to calculate the initial amplitudes of each Gaussian component. At last the waveform is fitted with the chosen and ranked Gaussians by Levenberg-Marquardt method, achieving basic optimized parameters of Gaussians. Three types of simulated return waveforms of the laser altimeter from scalariform terrain, woodland and slope surface have been fitted by this decomposing algorithm, the original waveforms are successfully approximated by the fitted ones and the optimized parameters of simulated return waveforms are satisfied. And the results prove that the decomposing algorithm of laser altimeter waveforms obtains a higher precision, it will have a good effect on the analysis of laser altimeter return waveforms.