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Decomposition of laser altimeter waveforms

372

Citations

9

References

2000

Year

TLDR

The authors propose a method to decompose laser altimeter return waveforms into Gaussian components for estimating the mean elevation of individual reflecting surfaces. They model each waveform component as a Gaussian, estimate the number of components from smoothed inflection points, initialize parameters from these points, rank components by width and amplitude, and iteratively optimize selected Gaussians with Levenberg–Marquardt, adding more if necessary to meet accuracy. The method was validated on airborne LVIS data collected over Sequoia National Forest in October 1997.

Abstract

The authors develop a method to decompose a laser altimeter return waveform into a series of components assuming that the position of each component within the waveform can be used to calculate the mean elevation of a specific reflecting surface within the laser footprint. For simplicity, they assume each component is Gaussian in nature. They estimate the number of Gaussian components from the number of inflection points of a smoothed copy of the laser waveform and obtain initial estimates of the Gaussian half-widths and positions from the positions of its consecutive inflection points. Initial amplitude estimates are obtained using a nonnegative least-squares method (LSM). To reduce the likelihood of fitting the background noise within the waveform and to minimize the number of Gaussians needed in the approximation, we rank the "importance" of each Gaussian in the decomposition using its initial half-width and amplitude estimates. The initial parameter estimates of all Gaussians ranked "important" are optimized using the Levenburg-Marquardt method. If the sum of the Gaussians does not approximate the return waveform to a prescribed accuracy, then additional Gaussians can be included in the optimization procedure or initial parameters can be recalculated. The Gaussian decomposition method is demonstrated on data collected by the airborne laser vegetation imaging sensor (LVIS) in October 1997 over the Sequoia National Forest, California.

References

YearCitations

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