LIDAR full-waveform data analysis for detection of faint returns through obscurants

摘要

Innovative algorithm development for fall-waveform lidar data processing extends this remote sensing technology's capabilities to even more complicated acquisition scenarios then previously determined, namely success of surveys over obscured areas. Waveform decomposition and the extraction of waveform metrics provide a straightforward approach to identifying vertical structure within each laser measurement. However, there are some limitations in this approach as faint returns within the waveform go undetected in the processing chain. These faint returns are the result of reduced energy levels due to obscurant scattering, attenuation and absorption. Lidar surveys over non-homogeneous wooded regions indicate that there are meaningful ground returns within dense tree coverage if extracted correctly from the data. One difficulty associated with detecting weaker returns is the presence of a hardware induced ring by the Avalanche Photo Diode (APD) detector in the returned waveform. By using a waveform stacking technique with adjacent waveforms in near geospatial proximity to the original, these faint returns can be augmented and detected during data processing without the inclusion of the false ring. In comparison to the traditional approach, the waveform stacking technique provides a 9% increase in faint signal extraction for the particular dataset. These faint signals are low level last returns that correspond to perceived ground reflections under canopy cover. The enhanced capability in the presence of foliage provides a decrease in operational effort associated with data density, dwell or targeting techniques and survey expense.