Polarimetric Modeling using a Computationally Efficient Physics-Based Tool
Department of Energy
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1485 South Main Street, Blacksburg, VA, 24073
Socially and Economically Disadvantaged:
AbstractGlobal monitoring for nonproliferation of weapons of mass destruction typically involves standoff detection through remote sensing technologies (radar, ladar, optical imaging, etc.). A backscattered radar or optical waveform contains information in its amplitude, phase, and polarization as well as in its time response (range resolution) and azimuthal resolution (related to the beamwidth). This over¬abundance of data requires real-time processing to rapidly scan a volume for hidden targets. This project will develop technology to rapidly predict polarimetric forward scattering: when the transform of the incident waveform is introduced, the solution for scattering from a hidden target is rapidly obtained for a time-domain waveform propagating and scattering in a random medium. The approach will build upon an existing physics-based, reduced-order, time-domain vector radiative transfer (VRT) algorithm for predicting time-domain polarimetric radar or ladar/lidar return waveforms from a random medium surrounding an embedded target. The new solution technique will be integrated into a profile inversion framework for target detection and identification. Commercial Applications and other Benefits as described by the awardee: Improved target detection and feature extraction would allow for a more rapid search and evaluation of data to enforce the nonproliferation of weapons of mass destruction. Similarly, law enforcement, search and rescue, and border patrol personnel could use the rapid data analysis and waveform design capabilities to cover large areas, in order to find lost personnel, stolen and hidden cargo, vehicles, and weapons from stand-off distances. Commercially, this same technology could be used to support imaging systems in the multi-billion dollar medical imaging field and in the nondestructive evaluation of civil structures and commercial vehicles.
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