Paper
9 June 2014 Improving waveform lidar processing toward robust deconvolution of signals for improved structural assessments
Kerry Cawse-Nicholson, Jan van Aardt, Shea Hagstrom, Paul Romanczyk, Crystal Schaaf, Alan Strahler, Zhan Li, Keith Krause
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Abstract
In a typical waveform light detection and ranging (lidar) system, the received pulse can be represented by the convolution of the system impulse response, the outgoing pulse, and the underlying signal representing actual target interactions. Deconvolution is the process of removing the contribution of the system impulse response and outgoing pulse from the received signal, so that the true interactions may be seen. In many examples, deconvolution has been shown to expose fine structure within the waveform, which may be used to improve accuracy when estimating the vertical location of certain features. For instance, the exact location of the ground may be more accurately determined by separating the response of the ground from that of understory vegetation or vegetative ground cover. However, in order for the deconvolution to be successful, the impulse response and outgoing pulse must be known, and many deconvolution methods are sensitive to small errors in the estimation of these inputs. In this study, we propose a deconvolution method that uses a flat target response in place of the impulse response and outgoing pulse.
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Kerry Cawse-Nicholson, Jan van Aardt, Shea Hagstrom, Paul Romanczyk, Crystal Schaaf, Alan Strahler, Zhan Li, and Keith Krause "Improving waveform lidar processing toward robust deconvolution of signals for improved structural assessments", Proc. SPIE 9080, Laser Radar Technology and Applications XIX; and Atmospheric Propagation XI, 90800I (9 June 2014); https://doi.org/10.1117/12.2050577
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Cited by 5 scholarly publications.
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KEYWORDS
Deconvolution

LIDAR

Convolution

Signal processing

Observatories

Denoising

Imaging systems

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