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Lookup NU author(s): Yu-Ching Lin,
Professor Jon Mills,
Dr Sarah Smith-Voysey
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Current discrete airborne laser scanning (ALS) systems suffer from a limited number of multiple returns and the loss of information about range estimation. To improve range resolution and accuracy, latest generation small-footprint, full-waveform laser scanning data were investigated and an approach developed to determine the number of targets within complex waveforms. The approach, termed rigorous Gaussian detection (RGD), is based on the popular Gaussian decomposition method but is implemented with rigorous estimates of initial values and a sophisticated iteration procedure. Second derivatives of waveforms and the number of samples on the edges of visible peaks were analysed to find overlapping targets. Weak pulses were detected where the residuals of Gaussian fitting were high and corresponding pulse widths were close to that of the transmitted pulse. The performance was compared with two other pulse detection techniques from commercial software, namely the centre of gravity (COG) method and the Gaussian pulse fitting (GPF) method with the Levenberg-Marquardt iterative algorithm. The results proved that the developed pulse detection method resolved multi-targets well. For example, in a sample of 201 dual-target waveforms, the RGD method correctly detected two targets in all the samples, considerably outperforming the COG and GPF methods, which achieved 57% and 67% success rates, respectively. When measuring the target heights using the different methods, the RGD method, with a root mean square error (RMSE) of 0.06 m, proved twice as accurate as the next best method, COG. The developed approach therefore compares favourably against the two commercial pulse detection methods considered, where their failure to detect hidden targets within complex waveforms and weak pulses resulted in a decrease of multi-target resolution, unreliable three-dimensional (3D) points, and also the loss of information from weak pulses.
Author(s): Lin YC, Mills JP, Smith-Voysey S
Publication type: Article
Publication status: Published
Journal: International Journal of Remote Sensing
Print publication date: 01/02/2010
ISSN (print): 0143-1161
ISSN (electronic): 1366-5901
Publisher: Taylor & Francis Ltd.
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