Digital Pulse Processing Methods for Range Refinement of LADAR Systems
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This paper presents several data processing techniques to resolve the time of flight from digitized light pulses received by a state of the art scanning LADAR system called HD6D. The challenges in the wave form identification and peak-to-peak distance quantification are outlined. Algorithms to identify appropriate cases from digitized samples are outlined and the most challenging case of overlapping wave forms is detailed. For the challenging case of overlapping waves, two distinct algorithms are proposed to estimate the peak to peak distance. First approach known as XCURV uses a sum of two exponential functions to model the over-lapping wave forms. A nonlinear least squares algorithm is used to estimate the unknown distance between the peaks along with the amplitude ratios of the waves recorded. Second approach uses a cubic spline fit to the data to estimate the area under the curve. It is shown that the centroid computation of the spline fit is equivalent to a weighted average of the measurement points of interest. Numerical simulations and experimental results are presented for both algorithms.