Examination of Count-Starved Gamma Spectra Using the Method of Spectral Comparison Ratios

Pfund, David M.; Runkle, Robert C.; Anderson, Kevin K.; Jarman, Kenneth D.

doi:10.1109/tns.2007.901202

Cited by 44 publications

(46 citation statements)

References 6 publications

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“…The background estimation algorithm described herein assumes that the effect on threat detection metrics from benign nuisance sources of radiation, such as medical isotopes, can be taken into account by the consuming anomaly detection or source localization module, using nuisance-rejection as described in [1].…”

Section: Nuclear Instruments and Methods Inmentioning

confidence: 99%

“…As an intermediate step to estimate the background spectrum, the current algorithm estimates the K, U, and T soil concentrations, namely c K (%), c U (ppm), and c T (ppm), respectively, using matrix equation (1), of the form n 3 Â 1 ¼ S 3X3 c 3 Â 1 . …”

Section: Methodsmentioning

confidence: 99%

“…Background estimations from the current algorithm will be used as input, to provide a baseline for anomaly detection [1] and localization [2] algorithms.…”

Section: Introductionmentioning

confidence: 99%

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Real-time airborne gamma-ray background estimation using NASVD with MLE and radiation transport for calibration

Kulisek

Schweppe

Stave

et al. 2015

Nuclear Instruments and Methods in Physics Research Section A:

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a b s t r a c tHelicopter-mounted gamma-ray detectors can provide law enforcement officials the means to quickly and accurately detect, identify, and locate radiological threats over a wide geographical area. The ability to accurately distinguish radiological threat-generated gamma-ray signatures from background gamma radiation in real time is essential in order to realize this potential. This problem is non-trivial, especially in urban environments for which the background may change very rapidly during flight. This exacerbates the challenge of estimating background due to the poor counting statistics inherent in real-time airborne gamma-ray spectroscopy measurements. To address this challenge, we have developed a new technique for real-time estimation of background gamma radiation from aerial measurements without the need for human analyst intervention. The method can be calibrated using radiation transport simulations along with data from previous flights over areas for which the isotopic composition need not be known. Over the examined measured and simulated data sets, the method generated accurate background estimates even in the presence of a strong, 60 Co source. The potential to track large and abrupt changes in background spectral shape and magnitude was demonstrated. The method can be implemented fairly easily in most modern computing languages and environments.

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Section: Nuclear Instruments and Methods Inmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Real-time airborne gamma-ray background estimation using NASVD with MLE and radiation transport for calibration

Kulisek

Schweppe

Stave

et al. 2015

Nuclear Instruments and Methods in Physics Research Section A:

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“…Previous source search methods have focused on detecting radioactive sources with a mobile detector when a previous radiological survey does not exist (Runkle et al, 2007;Jarman et al, 2010). Without previous knowledge of the background radiation spectrum, these systems must distinguish changes caused by man-made sources from natural variation in the background, reducing their sensitivity.…”

Section: Background On Radiological Surveymentioning

confidence: 99%

“…In border security, they can be used as part of a protocol to scan for illicit radiological material on trucks at a border crossing or container ships at a port. In disaster response, they can be used to help assess the radiological impact of nuclear accidents such as Chernobyl or Fukushima (Lyons and Colton, 2012).Previous source search methods have focused on detecting radioactive sources with a mobile detector when a previous radiological survey does not exist (Runkle et al, 2007;Jarman et al, 2010). Without previous knowledge of the background radiation spectrum, these systems must distinguish changes caused by man-made sources from natural variation in the background, reducing their sensitivity.…”

mentioning

confidence: 99%

Multiscale Spatial Density Smoothing: An Application to Large-Scale Radiological Survey and Anomaly Detection

Tansey

Athey

Reinhart

et al. 2017

Journal of the American Statistical Association

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We consider the problem of estimating a spatially varying density function, motivated by problems that arise in large-scale radiological survey and anomaly detection. In this context, the density functions to be estimated are the background gamma-ray energy spectra at sites spread across a large geographical area, such as nuclear production and waste-storage sites, military bases, medical facilities, university campuses, or the downtown of a city. Several challenges combine to make this a difficult problem. First, the spectral density at any given spatial location may have both smooth and nonsmooth features. Second, the spatial correlation in these density functions is neither stationary nor locally isotropic. Finally, at some spatial locations, there is very little data. We present a method called multiscale spatial density smoothing that successfully addresses these challenges. The method is based on recursive dyadic partition of the sample space, and therefore shares much in common with other multiscale methods, such as wavelets and Pólya-tree priors. We describe an efficient algorithm for finding a maximum a posteriori (MAP) estimate that leverages recent advances in convex optimization for non-smooth functions.We apply multiscale spatial density smoothing to real data collected on the background gamma-ray spectra at locations across a large university campus. The method exhibits state-of-the-art performance for spatial smoothing in density estimation, and it leads to substantial improvements in power when used in conjunction with existing methods for detecting the kinds of radiological anomalies that may have important consequences for public health and safety.Key words: radiological survey, density estimation, spatial statistics, Bayesian nonparametrics, total-variation denoising, fused lasso IntroductionLost or stolen radioactive sources present a challenging security problem. Widely used for industrial radiography, sterilization, and medical imaging, these sources are often poorly secured (Gaffigan, 2012) and sometimes stolen (Korshukin and Emery, 2006). To prevent dangerous accidents and to detect radiological dispersal devices (dirty bombs) before they can be used, security agencies are interested in continuously monitoring wide areas for radiation sources. A simple method is to monitor overall radiation levels. But these vary naturally in space, as different soil, stone, and building materials can contain widely different amounts of naturally occurring radioactive materials (NORM). Moreover, different detectors exhibit very different overall sensitivities to radiation. It is therefore more effective to monitor the energy spectrum of the detected radiation instead, as different radioactive materials emit gamma radiation at distinct energies.But to find a spectral anomaly, one must first know what the normal background spectrum looks like at all spatial locations. The background spectrum is the probability distribution for the energy of a gamma ray emitted by natural sources of radiation at a g...

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Time series evaluation of radiation portal monitor data for point source discrimination

Robinson

Bender

Flumerfelt

et al. 2009

J Radioanal Nucl Chem

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Examination of Count-Starved Gamma Spectra Using the Method of Spectral Comparison Ratios

Cited by 44 publications

References 6 publications

Real-time airborne gamma-ray background estimation using NASVD with MLE and radiation transport for calibration

Real-time airborne gamma-ray background estimation using NASVD with MLE and radiation transport for calibration

Multiscale Spatial Density Smoothing: An Application to Large-Scale Radiological Survey and Anomaly Detection

Time series evaluation of radiation portal monitor data for point source discrimination

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