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An Improved Classification Scheme for Standoff Detection of Explosives via Raman Spectroscopy
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2010 (English)Conference paper, (Refereed) Published
Abstract [en]

Raman spectroscopy is a laser-based vibrational tech- nique that can provide spectral signatures unique to a multitude of compounds. The technique is gaining widespread interest as a method for detecting hidden explosives due to its sensitivity and ease of use. In this work, we present a computationally e±cient clas- si¯cation scheme for accurate stando® identi¯cation of several common explosives using visible-range Raman spectroscopy. Using real measurements, we evaluate and modify a recent correlation-based approach to classify Raman spectra from various both harmful and commonplace substances. The results show that the proposed approach can, at a distance of 30 me- ters, or more, successfully classify measured Raman spectra from several explosive substances, including Nitromethane, TNT, DNT, Hydrogen Peroxide, TATP and Ammonium Nitrate.

Place, publisher, year, edition, pages
Aalborg: Eurasip , 2010.
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:bth-7548Local ID: oai:bth.se:forskinfoE0EE4B0620B4A4FAC12578AF0040A583OAI: oai:DiVA.org:bth-7548DiVA: diva2:835173
Conference
18th European Signal Processing Conference, EUSIPCO
Available from: 2012-09-18 Created: 2011-06-14 Last updated: 2015-06-30Bibliographically approved

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