Phase II year
2023
(last award dollars: 1723975421)
Phase II Amount
$1,315,112
Optical detection of objects hidden behind opaque layers is a challenging problem. As such, Person-Borne Improvised Explosive Devices (PB-IEDs) underneath clothing continue to be a persistent threat to the military and law enforcement communities. Safe stand-off detection in crowds is needed for the confirmation, identification, and neutralization of PB-IEDs. Technologies previously investigated include terahertz, millimeter wave, x-ray, radar, and LWIR, however several factors, such as performance, cost, lack of covertness, have prevented wide scale implementation of these technologies. Recent studies on the imaging spectroscopic measurement of cloth fabrics with visible and SWIR Hyperspectral Imaging (HSI) instrument suggests that this spectral region for PB-IED detection presents its potential for detecting object under fabric materials. The proposed approach to counter PB-IED is based on Acousto-Optic Tunable Filter (AOTF) and Liquid Crystal Variable Retarder (LCVR)-based Polarimetric HSI (PHSI), to detect, identify, and visualize hidden objects under the cloth with analysis of PHSI data with deep learning algorithms in real time.
