4 May 2012 Physics-based, reduced-order gas cloud with radiative transport model for rapid simulation of hyperspectral infrared sensors
Peter A. Kottke, Andrei G. Fedorov
Author Affiliations +
Abstract
We have developed a reduced-order, physics-based model of gas cloud transport and combined it with an approximate formulation of the equation of radiative transport to enable efficient prediction of spectral irradiation for simulation of hyperspectral infrared sensors. The resulting combined model is easily implemented, providing a rapid and flexible in silico experimentation capability. The gas cloud model is based on the entrainment hypothesis and predicts cloud trajectories in three-dimensions, with elevation changes occurring primarily due to buoyancy effects and with spreading and accompanying dilution and cooling occurring due to a turbulence dominated growth mechanism. The radiation transport model is simplified through an approximate treatment of scattering that transforms the governing equation from an integro-differential equation to an ordinary differential equation. The conjugate model has been combined with a simple sensor model and has been validated through comparison to results from large-scale field tests. The utility of the simulations has also been demonstrated through inclusion in a larger algorithm development and analysis program, the chem/bio algorithm development kit.
© 2012 Society of Photo-Optical Instrumentation Engineers (SPIE) 0091-3286/2012/$25.00 © 2012 SPIE
Peter A. Kottke and Andrei G. Fedorov "Physics-based, reduced-order gas cloud with radiative transport model for rapid simulation of hyperspectral infrared sensors," Optical Engineering 51(5), 056401 (4 May 2012). https://doi.org/10.1117/1.OE.51.5.056401
Published: 4 May 2012
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Cited by 1 scholarly publication.
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KEYWORDS
Clouds

Sensors

Computer simulations

Atmospheric modeling

Infrared sensors

Data modeling

Scattering

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