Comparison Analysis of Five Waveform Decomposition Algorithms for the Airborne LiDAR Echo Signal

The information from the components obtained by waveform decomposition is usually used to inverse topography, and classify tree species, etc. Many efforts on algorithms have been presented, but they lack comparison analysis evaluation. Thereby, this article compares analyzes performance of five algorithms, which are Gaussian, Adaptive Weibull, Richardson–Lucy (RL), Gold, under different topographic conditions such as forests, glaciers, lakes, residential areas. experimental results reveal that: first, Gaussian algorithm causes biggest fitting error at 9.96 mV in forested area. It easy identify multiple dense peaks single peaks. Second, there many misjudged, superimposed, overlapped separated Weibull algorithm. more capable complex waveforms has 122 outliers than does. Third, Gold RL decompose largest number (272.2k 265.9k) area; both can effectively improve separability Fourth, only effective for area with sparse vegetation does, i.e., processing data areas a lowest false component detection rate 1.3%, 0.9%, 1.1%, 0.1% four Finally, much faster speed 1000/s 2000/s other three do. These useful selecting environments.