You have requested a machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Neither SPIE nor the owners and publishers of the content make, and they explicitly disclaim, any express or implied representations or warranties of any kind, including, without limitation, representations and warranties as to the functionality of the translation feature or the accuracy or completeness of the translations.
Translations are not retained in our system. Your use of this feature and the translations is subject to all use restrictions contained in the Terms and Conditions of Use of the SPIE website.
5 May 2010Estimation and discrimination of aerosols using multiple wavelength LWIR lidar
This paper presents an overview of recent work by the Edgewood Chemical Biological Center (ECBC) in
algorithm development for parameter estimation and classification of localized atmospheric aerosols using
data from rapidly tuned multiple-wavelength range-resolved LWIR lidar. The motivation for this work is
the need to detect, locate, and discriminate biological threat aerosols in the atmosphere from interferent
materials such as dust and smoke at safe standoff ranges using time-series data collected at a discrete set of
CO2 laser wavelengths. The goals of the processing are to provide real-time aerosol detection, localization,
and discrimination. Earlier work by the authors has produced an efficient Kalman filter-based algorithm
for estimating the range-dependent aerosol concentration and wavelength-dependent backscatter signatures.
The latter estimates are used as feature vectors for training support vector machines classifiers for
performing the discrimination. Several years of field testing under the Joint Biological Standoff Detection
System program at Dugway Proving Ground, UT, Eglin Air Force Base, FL, and other locations have
produced data and backscatter estimates from a broad range of biological and interferent aerosol materials
for the classifier development. The results of this work are summarized in our presentation.
The alert did not successfully save. Please try again later.
Russell E. Warren, Richard G. Vanderbeek, Jeffrey L. Ahl, "Estimation and discrimination of aerosols using multiple wavelength LWIR lidar," Proc. SPIE 7665, Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XI, 766504 (5 May 2010); https://doi.org/10.1117/12.850077