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Progress in LIBS for land mine detection / by Jennifer L. Gottfried, Russell S. Harmon, and Aaron LaPointe.

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Format:
Book
Government document
Author/Creator:
Gottfried, Jennifer L.
Contributor:
Harmon, R. S. (Russell S.)
LaPointe, Aaron
U.S. Army Research Laboratory
Series:
ARL-TR (Aberdeen Proving Ground, Md.) ; 5127.
ARL-TR ; 5127
Language:
English
Subjects (All):
Land mines--Detection--Research.
Land mines.
Laser-induced breakdown spectroscopy--Research.
Laser-induced breakdown spectroscopy.
Physical Description:
1 online resource (iv, 18 pages) : color illustrations.
Other Title:
Progress in laser-induced breakdown spectroscopy (LIBS) for land mine detection
Place of Publication:
Aberdeen Proving Ground, MD : Army Research Laboratory, [2010]
Summary:
"The ability to interrogate objects buried in soil and ascertain their chemical composition in-situ would be an important capability enhancement for both military and humanitarian demining. Laser-induced breakdown spectroscopy (LIBS) is a simple spark spectrochemical technique using a pulsed laser. Recent developments in broadband and man-portable LIBS provide the capability for the real-time detection of all elements at very high sensitivity in any target material. This technological advance offers a unique potential for the development of a rugged and reliable man-portable or robot-deployable chemical sensor that would be capable of both in-situ point probing and chemical sensing for land mine detection. In this study, broadband LIBS spectra were acquired under laboratory conditions for more than a dozen different types of antipersonnel and antitank land mine casings from four countries. A set of antitank land mine simulants was also acquired. Subsequently, a statistical classification technique (partial least-squares discriminant analysis) was used to discriminate land mine casings from the simulants and to assign 'unknown' spectra to a mine type based upon a library classification approach. Overall, a correct classification success of 99.0% was achieved, with a misclassification rate of only 1.8%."--Page ii.
Notes:
Title from PDF title screen (ARL, viewed Dec. 14, 2010).
"April 2010."
Includes bibliographical references.
OCLC:
696018760

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