Truth Quest: Enabling Operational/Exercise Data

"Much of the focus of the ATR effort has focused on target definition within a test site. Synthetic Aperture Radar (SAR) has demonstrated great potential to precisely identify metal-based targets under precise conditions. Though SAR excels in this area,it is far less useful for predicting vegetative, geologic and non-metallic anthropogenic confusion, the forte of hyperspectral data. Using hyperspectral imagery, which records reflectance in 100 plus bands across the visible to middle infrared spectralrange, fused with SAR provides a unique opportunity to significantly enhance the ATR capability of the current SAR-based approach. The project demonstrates how hyperspectral data can contribute to (1) precisely identifying targets located throughout thelandscape using hyperspectral imagery to compliment MSTAR target identification, (2) demonstrate the use of high resolution hyperspectral imagery to precisely identify and classify confusion, (3) develop the algorithms and processes necessary to preciselyanalyze (atmospherically correct, geometrically correct, read and archive, classify and process for integration) using a range of software, existing algorithms, and new algorithms to fuse SAR, hyperspectral and other remotely sensed optical and radar datasets in order to significantly enhance ATR capability across the landscape. The technology will result in new improved methods to precisely detect, measure and describe targets within a