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10 May 2012 Schedule optimization for IR detection of buried targets
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Abstract
Schedule optimization of air platforms for IR sensors is a priority because of 1) the time sensitive nature of the IR detection of buried targets, 2) limited air platform assets, and 3) limited bandwidth for live-feed video. Scheduling optimization for airborne IR sensors depends on transient meteorological predictions, transient soil properties, target type and depth. This work involves using predictions from the Weather Research and Forecasting (WRF) model, a regional weather model, as input to the Countermine Computational Test Bed (CTB), a 3D finite element model that accounts for coupled heat and moisture transfer in soil and targets. The result is a continuous 2-day optimized schedule for airborne IR assets. In this paper, a 2-day optimized schedule for an airborne IR sensor asset is demonstrated for a single geographical location with a buried target. Transient physical surface and subsurface soil temperatures are presented as well as the phase-shifted, transient thermal response of the target.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zenon Derzko, John B. Eylander, and J. Thomas Broach "Schedule optimization for IR detection of buried targets", Proc. SPIE 8357, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVII, 83570N (10 May 2012); https://doi.org/10.1117/12.918490
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