星载激光测高系统在应用于冠层高度反演时，由于光斑尺寸较大、地表环境复杂等因素，导致无法准确地从回波信号中提取地面位置。针对该问题，设计了一种分类地面波形，计算有效候选峰加权高程的地面返回位置提取和植被冠层高度反演方法。采用该方法对佛蒙特州西北地区的GLAS回波数据进行了处理，实现了地面高程提取和冠层高度反演，以同时期机载Lidar测量数据进行精度验证，并与高斯分解法的反演结果进行比较。结果表明该方法提取的地面返回位置与机载雷达采集的地面点云的分布非常接近，且地面提取精度优于高斯分解法；GLAS冠层高度反演结果RMSE为2.82 m，相关系数为0.81，与机载激光雷达测量结果具有较好的一致性，且优于高斯分解法的冠层高度反演结果。

When applied to the canopy height inversion, the spaceborne laser altimetry system cannot accurately extract the ground position from the echo signal due to factors such as large spot size and complex surface. Aiming at this problem, a new ground return position extraction and vegetation canopy height inversion algorithm was designed to classify the ground waveform and calculate the weighted elevation of effective candidate peak. The geoscience laser altimeter system (GLAS) echo data in the northwestern region of Vermont was processed by this method,so as to realize the ground elevation extraction and canopy height inversion. And the processing results were verified by the Lidar measurement data during the same period, as well as compared with the inversion results of Gaussian decomposition method. The results show that the ground return position extracted by the proposed method is very close to the distribution of ground point cloud collected by the airborne Lidar, and the ground extraction accuracy is better than that of the Gaussian decomposition method. The root-mean-square error (RMSE)and correlation coefficient of GLAS canopy height inversion result are respectively 2.82 m and 0.81, which are in good consistency with those of the airborne laser Lidar and superior to those of the Gaussian decomposition.