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Proceedings Paper

Progress in LIBS for landmine detection
Author(s): Jennifer L. Gottfried; Russell S. Harmon; Aaron La Pointe
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Paper Abstract

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 at very high sensitivity of all elements in any target material because all chemical elements emit in the 200-940 nm spectral region. 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 landmine detection. Broadband LIBS data was acquired under laboratory conditions for more than a dozen different types of anti-personnel and anti-tank landmine casings from four countries plus a set of antitank landmine simulants. Subsequently, a statistical classification technique (partial least squares discriminant analysis, PLS-DA) was used to discriminate landmine 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%. This performance illustrates the potential that LIBS has to be developed into a field-deployable device that could be utilized as a confirmatory sensor in landmine detection. The operational concept envisioned is a small LIBS system that is either man-portable or robot-deployed in which a micro-laser is contained in the handle of a deminer's probe, with laser light delivered and collected through an optical fiber in the tapered tip of the probe. In such a configuration, chemical analysis could be readily accomplished by LIBS after touching the buried object that one is interested in identifying and using real-time statistical signal processing techniques to accomplish "mine/no-mine" discrimination and even object identification if a material library could be constructed prior to analysis.

Paper Details

Date Published: 5 May 2009
PDF: 11 pages
Proc. SPIE 7303, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIV, 73031F (5 May 2009); doi: 10.1117/12.818286
Show Author Affiliations
Jennifer L. Gottfried, Army Research Lab. (United States)
Russell S. Harmon, Army Research Office (United States)
Aaron La Pointe, U.S. Army Night Vision & Electronic Sensors Directorate (United States)

Published in SPIE Proceedings Vol. 7303:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIV
Russell S. Harmon; J. Thomas Broach; John H. Holloway, Editor(s)

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