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Time Correlation Enhanced Stand Off Raman Detection

Award Information
Agency: Department of Defense
Branch: Army
Contract: W911NF-06-C-0039
Agency Tracking Number: A052-038-1981
Amount: $69,996.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: A05-038
Solicitation Number: 2005.2
Timeline
Solicitation Year: 2005
Award Year: 2005
Award Start Date (Proposal Award Date): 2005-12-10
Award End Date (Contract End Date): 2006-05-09
Small Business Information
2520 W. 237th Street
Torrance, CA 90505
United States
DUNS: 033449757
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Glenn Bastiaans
 Senior Scientist
 (310) 530-7130
 sbirproposals@intopsys.com
Business Contact
 Lothar Kempen
Title: Vice President, R&D
Phone: (310) 530-7130
Email: lkempen@intopsys.com
Research Institution
N/A
Abstract

Intelligent Optical Systems (IOS) proposes to develop a novel, highly sensitive stand-off detector for trace amounts of explosives. The most promising stand-off detection schemes for explosive residues are optical in nature but are limited in both sensitivity and range. The essential problem is in the light detection components and the signal processing algorithms, which do not allow sufficient signal to noise discrimination. Applying IOS' experience in Optical Time Domain Reflectometry (OTDR) signal processing, it will be possible to extend the sensitivity of existing stand-off Raman spectroscopy residue detection systems by two orders of magnitude, extending the stand-off detection range by as much as an order of magnitude. Principal component analysis of the spectra, which IOS is already applying to concealed explosives detection, will provide rapid and unambiguous identification of even multiple component explosives residue. What distinguishes IOS is the way that IOS processes OTDR signals. It has already been shown that stand-off Raman spectroscopy works for explosive residue detection, though it currently lacks sensitivity. OTDR signal processing is also well known. IOS will combine these two approaches, and demonstrate that, by using time-correlation spectroscopy, we can digitally extract extremely small signals from a background many orders of magnitude larger.

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

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