The SSI active sensing group is involved with the extraction of material identification, surface properties, sub-surface defects and voids, and overall target identification and assessment via remote sensing.
The approach is the application of fundamental physics to sufficiently characterize sensors and the interaction of radiation with targets to capture important identifying features and conditions from the remote sensing process.
In addition, forefront mathematical algorithms are applied to optimally process remotely sensed data towards these goals. These algorithms include statistics-based clustering for material identification, multi-view tomographic algorithms for target reconstruction, 3D SAR image reconstruction, and angle-independent robust multispectral processing.
Our diverse group of physicists and mathematicians have applied these principles to
Each area of active sensor R&D has resulted in special-purpose modeling and inversion codes that process the appropriate sensor data, including VIS/SWIR/TIR surface reconstruction (TRAILS), ultra wideband and wide aperture radar data (QUASAR), and gamma ray accelerator-based radiation for defect detection (HI-Z).
LADAR based reflection tomography from range profiles simulated for a UAV hardbody model. 1. A dual LADAR imaging scenario. 2. The Predator hard body model. 3. Tomographic reconstruction from simulated range profiles with 1 µ LADAR, 20 km range, and 20 cm beam width sweep on the target.