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Classification of Raman Spectra to Detect Hidden Explosives

Butt, Naveed LU ; Nilsson, Mikael; Jakobsson, Andreas LU ; Nordberg, Magnus; Pettersson, Anna; Wallin, Sara and Östmark, Henric (2011) In IEEE Geoscience and Remote Sensing Letters 8(3). p.517-521
Abstract
Raman spectroscopy is a laser-based vibrational technique 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 letter, we present a computationally efficient classification scheme for accurate standoff identification 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 harmful and commonplace substances. The results show that the proposed approach can, at a distance of 30 m, or more, successfully classify measured Raman spectra from several... (More)
Raman spectroscopy is a laser-based vibrational technique 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 letter, we present a computationally efficient classification scheme for accurate standoff identification 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 harmful and commonplace substances. The results show that the proposed approach can, at a distance of 30 m, or more, successfully classify measured Raman spectra from several explosive substances, including nitromethane, trinitrotoluene, dinitrotoluene, hydrogen peroxide, triacetone triperoxide, and ammonium nitrate. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Raman spectroscopy, explosives, detection, Correlation-bound
in
IEEE Geoscience and Remote Sensing Letters
volume
8
issue
3
pages
517 - 521
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
external identifiers
  • wos:000289899000027
  • scopus:79955524898
ISSN
1545-598X
DOI
10.1109/LGRS.2010.2089970
language
English
LU publication?
yes
id
db08f99f-a046-458c-819d-751e78bf6312 (old id 1691407)
date added to LUP
2011-07-14 09:27:04
date last changed
2017-10-29 03:17:27
@article{db08f99f-a046-458c-819d-751e78bf6312,
  abstract     = {Raman spectroscopy is a laser-based vibrational technique 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 letter, we present a computationally efficient classification scheme for accurate standoff identification 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 harmful and commonplace substances. The results show that the proposed approach can, at a distance of 30 m, or more, successfully classify measured Raman spectra from several explosive substances, including nitromethane, trinitrotoluene, dinitrotoluene, hydrogen peroxide, triacetone triperoxide, and ammonium nitrate.},
  author       = {Butt, Naveed and Nilsson, Mikael and Jakobsson, Andreas and Nordberg, Magnus and Pettersson, Anna and Wallin, Sara and Östmark, Henric},
  issn         = {1545-598X},
  keyword      = {Raman spectroscopy,explosives,detection,Correlation-bound},
  language     = {eng},
  number       = {3},
  pages        = {517--521},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  series       = {IEEE Geoscience and Remote Sensing Letters},
  title        = {Classification of Raman Spectra to Detect Hidden Explosives},
  url          = {http://dx.doi.org/10.1109/LGRS.2010.2089970},
  volume       = {8},
  year         = {2011},
}