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Multiple return separation for a full-field ranger via continuous waveform modellingFormat | Member Price | Non-Member Price |
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Paper Abstract
We present two novel Poisson noise Maximum Likelihood based methods for identifying the individual returns
within mixed pixels for Amplitude Modulated Continuous Wave rangers. These methods use the convolutional
relationship between signal returns and the recorded data to determine the number, range and intensity of returns
within a pixel. One method relies on a continuous piecewise truncated-triangle model for the beat waveform
and the other on linear interpolation between translated versions of a sampled waveform. In the single return
case both methods provide an improvement in ranging precision over standard Fourier transform based methods
and a decrease in overall error in almost every case. We find that it is possible to discriminate between two
light sources within a pixel, but local minima and scattered light have a significant impact on ranging precision.
Discrimination of two returns requires the ability to take samples at less than 90 phase shifts.
Paper Details
Date Published: 3 February 2009
PDF: 12 pages
Proc. SPIE 7251, Image Processing: Machine Vision Applications II, 72510T (3 February 2009); doi: 10.1117/12.805549
Published in SPIE Proceedings Vol. 7251:
Image Processing: Machine Vision Applications II
Kurt S. Niel; David Fofi, Editor(s)
PDF: 12 pages
Proc. SPIE 7251, Image Processing: Machine Vision Applications II, 72510T (3 February 2009); doi: 10.1117/12.805549
Show Author Affiliations
John P. Godbaz, The Univ. of Waikato (New Zealand)
Michael J. Cree, The Univ. of Waikato (New Zealand)
Michael J. Cree, The Univ. of Waikato (New Zealand)
Adrian A. Dorrington, The Univ. of Waikato (New Zealand)
Published in SPIE Proceedings Vol. 7251:
Image Processing: Machine Vision Applications II
Kurt S. Niel; David Fofi, Editor(s)
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