Range Estimation Algorithm Comparison in 3-D Flash LADAR Data

摘要

Peak, maximum likelihood (ML), and matched filter (MF) range estimation algorithms were tested in both simulated and measured 3-D Flash LADAR data. A normalized version of the MF was also developed and tested. Three different methods based on averaging were developed to calibrate the pulse width of the reference waveform used in the MF and ML algorithms. Simulation results show that a MF produces a bias when waveforms are cropped or shifted off center within a range gate, but normalizing waveforms before computing the cross correlation can reduce the average bias. The ML algorithm also produces a bias in shifted waveforms based on their position within the range gate. The peak estimator suffers from high variance in measurements due to the effect of shot noise on waveforms. In the measured data sets, normalization did not reduce the bias in MF results because it increased the algorithm's sensitivity to errors in the reference waveform. The ML estimator resulted in the largest bias in the results and was attributed to an underlying flaw in the probability model based on a Gaussian waveform with Poisson noise.