Paper
7 November 2007 Waveform analysis of lidar data for targets in cluttered environments
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Abstract
In this paper we study the potential of using deconvolution techniques on full-waveform laser radar data for pulse detection in cluttered environments, e.g. when a land-mine is partly occluded by vegetation. A pulse width greater than the distance between the reflecting surfaces within the footprint results in a signal that is composed by overlapping reflections that may be very difficult to analyze successfully with standard pulse detection techniques. We demonstrate that deconvolution improves the chance of successful decomposition of waveform signals into the components corresponding to the reflecting objects in the path of the laser beam. Experimental data were analyzed in terms of pulse extraction capability and distance accuracy. It was found that deconvolution increases the pulse extraction performance, but that surfaces closer than about 40% of the laser pulse width are still very difficult to detect and that the number of spurious, erroneously extracted, points is the price to pay for increased pulse detection probability.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Gustav Tolt and Håkan Larsson "Waveform analysis of lidar data for targets in cluttered environments", Proc. SPIE 6739, Electro-Optical Remote Sensing, Detection, and Photonic Technologies and Their Applications, 67390A (7 November 2007); https://doi.org/10.1117/12.737237
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Cited by 5 scholarly publications.
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KEYWORDS
Deconvolution

Signal detection

Mining

Pulsed laser operation

Target detection

LIDAR

Sensors

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