Paper
26 April 2007 Detection and classification of atmospheric aerosols using multi-wavelength CO2 lidar
Author Affiliations +
Abstract
This paper presents an overview of recent work by ECBC in algorithm development for parameter estimation, detection, and classification of localized aerosols in the atmosphere using information provided by multiple-wavelength rangeresolved lidar. The motivation for this work is the need to detect, locate, and identify potentially toxic atmospheric aerosols at safe standoff ranges using time-series data collected at a discrete set of CO2 laser wavelengths. The goals of the processing are to use the digitized transmitted and received backscatter array data to (1) decide if significant aerosol is present, (2) provide estimates of the range and size of the aerosol cloud, (3) produce estimates of the backscatter spectral dependence, and (4) use the backscatter signatures as feature vectors for training and implementation of a support vector machine aerosol classifier. The paper describes examples this processing derived from an extensive set of data collected by ECBC during JBSDS field-testing at Dugway Proving Ground.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Russell E. Warren and Richard G. Vanderbeek "Detection and classification of atmospheric aerosols using multi-wavelength CO2 lidar", Proc. SPIE 6554, Chemical and Biological Sensing VIII, 65540V (26 April 2007); https://doi.org/10.1117/12.722414
Lens.org Logo
CITATIONS
Cited by 8 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Backscatter

Aerosols

LIDAR

Atmospheric particles

Data modeling

Filtering (signal processing)

Atmospheric sensing

Back to Top