全局收敛LM 的激光雷达波形数据分解方法

全波形激光雷达是遥感领域的新兴技术,相比传统激光雷达,它对后向散射回波进行全数字化的记录,通过分解返回波形能够得到更加丰富的地物属性信息,因此波形分解是激光雷达全波形数据处理的核心内容。针对传统LM算法容易陷入局部最优解的问题,提出一种全局收敛LM的激光雷达全波形数据分解方法。该方法引入全局收敛LM算法对波形进行拟合,获得波形分量参数的最优解,利用迭代的波峰检测策略实现复杂重叠波形分量的逐步分解。通过对GLAS、LVIS与Lite Mapper-5600的波形数据分解实验证明:该方法相比传统LM算法能够得到更具鲁棒性的波形分解结果,并且适用于星载波形数据、机载大光斑以及机载小光斑波形数据,具备较高实用价值。

Full-waveform LiDAR data decomposition method based on global convergent LM

Full-waveform LiDAR is a rising technique in the field of remote sensing. Compared with traditional LiDAR, it can digitize all the back-scattering pulses. More abundant attribute of targets shall be obtained by waveform decomposition, which is the core content of full-waveform lidar data processing. A waveform decomposition method based on global convergent LM was proposed. Waveform was fitted and optimal solutions of components' parameters were obtained by introducing global convergent LM. Decomposition of complex overlapping waveform components was realized by iterative peaks detection. The experimental results on GLAS, LVIS and Lite Mapper-5600 waveform data prove that, the decomposing results are more robust than traditional LM and proposed method is practical as it is suitable for satellite, airborne large footprint size and airborne small footprint size waveform data.