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Proceedings Paper

Phenomenology of prompt gamma neutron activation analysis in the detection of mines and near-surface ordnance
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Paper Abstract

Prompt gamma neutron activation analysis (PGNAA) has been proposed for confirming the presence of energetic materials as part of a mine or unexploded ordnance detection system. Ancore Corporation (previously SAIC Advanced Nucleonics Division), funded through Night Vision Electro Sciences Directorate by Environmental Security Test Certification Program, has carried out proof-of-concept demonstrations of PGNAA in this confirmatory role at Socorro, NM, and Yuma, AZ. In this, the first part of a two-part paper addressing the use of PGNAA in the detection of surface and near-surface UXO, we explore the phenomenology of PGNAA signals from surface or near-surface ordnance in soil to gain insight into the results of those demonstrations. PGNAA uses the high-energy gamma ray (10.8 MeV) from capture on N14 as a signature of the presence of nitrogen. This is one of the highest energy gamma rays resulting from neutron capture, and nitrogen is a major constituent of explosives, but a small portion of soil. Thus, PGNAA might be effective at confirming the presence of explosives. The phenomenology of dry soil is dominated by the two most common elements, oxygen and silicon. Neutrons injected into the soil elastically scatter from nuclei (predominantly oxygen), losing energy and propagating in a random walk fashion. Once slowed, neutron capture on soil elements produces a broad gamma-ray spectrum. Capture on Si29 produces a 10.6 MeV gamma, which is not resolvable from the nitrogen signal of interest using scintillation detectors. Thus, PGNAA will need either good resolution detectors, or robust background subtraction to estimate the silicon contribution. For any system unable to resolve the Si29 (10.6 MeV) and N14(10.8 MeV) gammas there is an inherently low signal to background, resulting primarily from the silicon in the soil. After background subtraction, there remains a challenging signal to noise level, where the noise is partly due to counting statistics and partly due to the modeling of the subtracted background.

Paper Details

Date Published: 4 September 1998
PDF: 8 pages
Proc. SPIE 3392, Detection and Remediation Technologies for Mines and Minelike Targets III, (4 September 1998); doi: 10.1117/12.324227
Show Author Affiliations
David A. Sparrow, Institute for Defense Analyses (United States)
Lisa J. Porter, Institute for Defense Analyses (United States)
J. Thomas Broach, U.S. Army Night Vision & Electronic Sensors Directorate (United States)
Roshni J. Mehta-Sherbondy, U.S. Army Night Vision & Electronic Sensors Directorate (United States)

Published in SPIE Proceedings Vol. 3392:
Detection and Remediation Technologies for Mines and Minelike Targets III
Abinash C. Dubey; James F. Harvey; J. Thomas Broach, Editor(s)

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