The U.S. military has been using satellite IR images to monitor ground missile activities of hostile nations. Successful IR monitoring of ground features requires us to account for the intervening weather conditions that can have an adverse impact on intelligence gathering. The proposed Self-Corrective Remote Imagery Prediction System (SCRIPS) will produce up to 72 hours of forecasts for any bandpass of IR imagery based on forecast mesoscale atmospheric conditions. The SCRIPS will integrate existing and well tested atmospheric models such as radiative transfer, atmospheric correction, and cloud masking. SCRIPS will also utilize forecast atmospheric state conditions from numerical weather prediction system. We will periodically improve the approach through adjustment of the radiative transfer model and updating the baseline image database. In the Phase I effort, we will incorporate a suitable atmospheric correction algorithm and an appropriate forward radiative transfer algorithm, select an appropriate mesoscale weather prediction product, prototype SCRIPS to predict IR images and to automatically update baseline database and adjust radiative transfer parameters.
Keywords: Ir Imagery, Sensor Management, Radiative Transfer Model, Forecast, Satellite
