Paper
29 May 2013 Methodology for the passive detection and discrimination of chemical and biological aerosols
William J. Marinelli, Kirill N. Shokhirev, Daisei Konno, David C. Rossi, Martin Richardson
Author Affiliations +
Abstract
The standoff detection and discrimination of aerosolized biological and chemical agents has traditionally been addressed through LIDAR approaches, but sensor systems using these methods have yet to be deployed. We discuss the development and testing of an approach to detect these aerosols using the deployed base of passive infrared hyperspectral sensors used for chemical vapor detection.

The detection of aerosols requires the inclusion of down welling sky and up welling ground radiation in the description of the radiative transfer process. The wavelength and size dependent ratio of absorption to scattering provides much of the discrimination capability. The approach to the detection of aerosols utilizes much of the same phenomenology employed in vapor detection; however, the sensor system must acquire information on non-line-of-sight sources of radiation contributing to the scattering process.

We describe the general methodology developed to detect chemical or biological aerosols, including justifications for the simplifying assumptions that enable the development of a real-time sensor system. Mie scattering calculations, aerosol size distribution dependence, and the angular dependence of the scattering on the aerosol signature will be discussed.

This methodology will then be applied to two test cases: the ground level release of a biological aerosol (BG) and a nonbiological confuser (kaolin clay) as well as the debris field resulting from the intercept of a cruise missile carrying a thickened VX warhead. A field measurement, conducted at the Utah Test and Training Range will be used to illustrate the issues associated with the use of the method.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
William J. Marinelli, Kirill N. Shokhirev, Daisei Konno, David C. Rossi, and Martin Richardson "Methodology for the passive detection and discrimination of chemical and biological aerosols", Proc. SPIE 8710, Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XIV, 87100B (29 May 2013); https://doi.org/10.1117/12.2015324
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KEYWORDS
Aerosols

Clouds

Sensors

Scattering

Atmospheric particles

Absorption

Atmospheric modeling

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