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Realtime PB-IED and Threat Detection With Spectro-Polarimetric Hyperspectral Camera

Award Information
Agency: Department of Defense
Branch: Army
Contract: W911SR-23-C-0025
Agency Tracking Number: A2-9576
Amount: $1,315,112.20
Phase: Phase II
Program: STTR
Solicitation Topic Code: NASA T8-01
Solicitation Number: N/A
Solicitation Year: 2014
Award Year: 2023
Award Start Date (Proposal Award Date): 2023-09-05
Award End Date (Contract End Date): 2025-09-04
Small Business Information
P.O. Box 616 19 Loveton Circle
Sparks, MD 21152-1111
United States
DUNS: 808275890
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Feng Jin
 (410) 472-7070
Business Contact
 Diane Murray
Phone: (936) 588-6901
Research Institution
P>D> Coverdell Center, 500 D.W. Brooks Drive
ATHENS, GA 30602-7394
United States

 (706) 363-0590
 Domestic Nonprofit Research Organization

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.

* Information listed above is at the time of submission. *

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