John P. Godbaz, Michael J. Cree, and Adrian A. Dorrington, "Multiple return separation for a full-field ranger via continuous waveform modelling," Image Processing: Machine Vision Applications II, Kurt S. Niel, David Fofi, Editors, Proc. SPIE, 7251, 72510T (2009).
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.
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