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Proceedings Paper

Estimating vapor concentration using range-resolved lidar with frequency-agile lasers
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Paper Abstract

Estimating the range dependence of vapor concentration with range-resolved lidar is a challenging problem because of the weak returns provided by atmospheric aerosols and the rapid decrease in signal-to-noise ratio with range. This paper summarizes an earlier approach for constructing a statistically optimal estimator for the range dependent vapor concentration using data from multiwavelength frequency-agile lidar. The estimates of path-integrated concentration from this algorithm are compared with those made using a previously derived Kalman filter on data collected by topographic backscatter from a mountain range. In addition, the range- resolved concentration estimation algorithm is generalized to the case of multiple vapor materials. The algorithms are illustrated on a combination of synthetic and field test data collected recently by SBCCOM at the Department of Energy Nevada Test Site.

Paper Details

Date Published: 30 November 1999
PDF: 10 pages
Proc. SPIE 3855, Air Monitoring and Detection of Chemical and Biological Agents II, (30 November 1999); doi: 10.1117/12.371271
Show Author Affiliations
Russell E. Warren, SRI International (United States)
Richard G. Vanderbeek, U.S. Army Soldier and Biological Chemical Command (United States)
Francis M. D'Amico, U.S. Army Soldier and Biological Chemical Command (United States)


Published in SPIE Proceedings Vol. 3855:
Air Monitoring and Detection of Chemical and Biological Agents II
Joseph Leonelli; Mark L.G. Althouse, Editor(s)

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