Point-Source Detection Using Gamma-Ray Spectra in Radiation-Portal Monitoring

Problem: Radiation detection systems are deployed at U.S. borders to guard against illicit entry of radioactive material. Unfortunately, nuisance alarms due to naturally occurring radioactive material (NORM) reduce detection probabilities for threat sources. This paper evaluates to what extent gamma...

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Bibliographic Details
Published in:Journal of quality technology 2013-07, Vol.45 (3), p.285-296
Main Authors: Burr, Tom, Hamada, Michael S., Myers, Kary, Skurikhin, Misha
Format: Article
Language:English
Subjects:
Detection alarms
Detection equipment
Energy
Gamma rays
Isotopes
Norms
Radiation
Radioactive materials
Radioactive substances
Sensors
Studies
Time series
Vehicles
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Summary:Problem: Radiation detection systems are deployed at U.S. borders to guard against illicit entry of radioactive material. Unfortunately, nuisance alarms due to naturally occurring radioactive material (NORM) reduce detection probabilities for threat sources. This paper evaluates to what extent gamma counts for a range of energies (i.e., a gamma spectrum) deployed in primary screening can detect threat-point sources, with attention to background-suppression effects. Approach: It is assumed that most NORM sources are more spatially distributed than a point source and that most threat sources are distributed more like a point source. Therefore, we seek a high-alarm probability for vehicle profiles that exhibit a point-like shift in spectral shape. The proposed approach uses variation of the gamma spectral shape over time as a moving vehicle carrying a point source is screened. Results: The paper uses data from approximately 2000 real vehicle screenings to develop alarm thresholds and to evaluate detection probabilities of injected threat sources from both NORM and threat isotopes. It is shown that transforming the raw gamma spectra is advantageous and that using the Mahalanobis distance to detect the point-like shift in spectral shape is superior to a spectral distance used in the literature. Key Words: Background Suppression; Mahalanobis Distance; Scan Statistic; Spectral Distance; Time Series.
ISSN:0022-4065
2575-6230
DOI:10.1080/00224065.2013.11917939