School of Remote Sensing and Information Engineering,Wuhan Universty,WuHan,China,School of Remote Sensing and Information Engineering,Wuhan Universty,WuHan,China,colllege of Electronical and Information Engineering, Inner Mongolia University,School of Life Science and Technology,Huazhong University of Science and Technology,WuHan,China,School of Life Science and Technology,Huazhong University of Science and Technology,WuHan,China
LiDAR (Light Detection and Ranging) waveform decomposition is a key issue in remote sensing data processing. Traditional waveform decomposition methods can’t detect weak sub-waveforms when sub-waveforms are overlapped in original data. Besides, these methods are time consuming and not robust to noise. To overcome the obstacle, this paper proposed a new method, which mainly includes four steps. The first is to estimate the errors by filtering the original waveform. Then, iteratively peeling off sub-waveforms from the waveforms till the value of maximum peak is less than a given threshold. The next step is to optimize the parameters of all sub-waveforms using L-BFGS method. At last, nearest sub-waveforms are combined. This new strategy can detect the weak peaks in the complex situations and is very robust to noise. Lots of experiments demonstrate the effectiveness of the proposed method.
LAI Xu-Dong, QIN Nan-Nan, HAN Xiao-Shuang, WANG Jun-Hong, HOU Wen-Guang. Iterative decomposition method for small foot-print LiDAR waveform[J]. Journal of Infrared and Millimeter Waves,2013,32(4):319~324Copy