Models to support active sensing of biological aerosol clouds

Andrea M. Brown; Jeffrey M. Kalter; Elizabeth C. Corson; Zahra Chaudhry; Nathan T. Boggs; David M. Brown; Michael E. Thomas; Christopher C. Carter

doi:10.1117/12.2016324

29 May 2013 Models to support active sensing of biological aerosol clouds

Andrea M. Brown, Jeffrey M. Kalter, Elizabeth C. Corson, Zahra Chaudhry, Nathan T. Boggs, David M. Brown, Michael E. Thomas, Christopher C. Carter

Author Affiliations +

Proceedings Volume 8710, Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XIV; 871013 (2013) https://doi.org/10.1117/12.2016324
Event: SPIE Defense, Security, and Sensing, 2013, Baltimore, Maryland, United States

Abstract

Elastic backscatter LIght Detection And Ranging (LIDAR) is a promising approach for stand-off detection of biological aerosol clouds. Comprehensive models that explain the scattering behavior from the aerosol cloud are needed to understand and predict the scattering signatures of biological aerosols under varying atmospheric conditions and against different aerosol backgrounds. Elastic signatures are dependent on many parameters of the aerosol cloud, with two major components being the size distribution and refractive index of the aerosols. The Johns Hopkins University Applied Physics Laboratory (JHU/APL) has been in a unique position to measure the size distributions of released biological simulant clouds using a wide assortment of aerosol characterization systems that are available on the commercial market. In conjunction with the size distribution measurements, JHU/APL has also been making a dedicated effort to properly measure the refractive indices of the released materials using a thin-film absorption technique and laboratory characterization of the released materials. Intimate knowledge of the size distributions and refractive indices of the biological aerosols provides JHU/APL with powerful tools to build elastic scattering models, with the purpose of understanding, and ultimately, predicting the active signatures of biological clouds.

Citation Download Citation

Andrea M. Brown, Jeffrey M. Kalter, Elizabeth C. Corson, Zahra Chaudhry, Nathan T. Boggs, David M. Brown, Michael E. Thomas, and Christopher C. Carter "Models to support active sensing of biological aerosol clouds", Proc. SPIE 8710, Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XIV, 871013 (29 May 2013); https://doi.org/10.1117/12.2016324

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