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Proceedings Paper

Estimation of vapor concentration in a changing environment
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Paper Abstract

A key limitation on the use of two-wavelength DIAL or its multi-spectral generalization is the unknown spectral structure of the topographically backscattered lidar signals in the absence of the target materials. Although some of the factors responsible for the background spectral structure can be measured in advance, others, such as the terrain differences are highly variable and usually unknown. For applications to tactical reconnainssance and high-altitude surveillance where the background is continuously changing, the inability to account for the background can seriously degrade sensor performance. This study describes a method for estimating both the spectral dependence of the background as well as the path-integrated concentration, or CL, from the same data set using dual Kalman filtering. The idea is to run parallel filters that estimate the background and CL using input from the other filter. The approach is illustrated on a variety of synthetic data sets and signal injections into background data collected by the U.S. Army WILDCAT sensor at Dugway Proving Ground.

Paper Details

Date Published: 15 August 2003
PDF: 8 pages
Proc. SPIE 5085, Chemical and Biological Sensing IV, (15 August 2003); doi: 10.1117/12.485782
Show Author Affiliations
Russell E. Warren, EO-Stat, Inc. (United States)
Richard G. Vanderbeek, U.S. Army Edgewood Chemical Biological Ctr. (United States)


Published in SPIE Proceedings Vol. 5085:
Chemical and Biological Sensing IV
Patrick J. Gardner, Editor(s)

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