Network algorithms for detection of radiation sources

Nageswara S.V. Rao; Satyabrata Sen; Nicholas J. Prins; Daniel A. Cooper; Robert J. Ledoux; James B. Costales; Krzysztof Kamieniecki; Steven E. Korbly; Jeffrey K. Thompson; James Batcheler; Richard R. Brooks; Chase Q. Wu

doi:10.1016/j.nima.2015.01.037

Network algorithms for detection of radiation sources

Nageswara S.V. Rao, Satyabrata Sen, Nicholas J. Prins, Daniel A. Cooper, Robert J. Ledoux, James B. Costales, Krzysztof Kamieniecki, Steven E. Korbly, Jeffrey K. Thompson, James Batcheler, Richard R. Brooks, Chase Q. Wu

Research output: Contribution to journal › Article › peer-review

39 Scopus citations

Abstract

Networks of radiation counters have been recently developed for detecting low-level, hazardous radiation sources, and they have been utilized in indoor and outdoor characterization tests. Subsequently, the test measurements have been "replayed" using multiple sub-networks, which enabled the analysis of various scenarios beyond the tests. We present a particle filter algorithm that combines measurements from gamma counters across the network to detect radiation sources. Using replays from an outdoor test, we construct a border monitoring scenario that consists of twelve 2 in.×2 in. NaI detectors or counters deployed on the periphery to monitor a 42×42 m² region. A ¹³⁷Cs source is moved across this region, starting several meters outside and finally moving away from it. The measurements from individual, pairs and boundary detectors are replayed using the particle filter algorithm. The algorithm outputs demonstrate, both quantitatively and qualitatively, the benefits of networking all boundary counters: the source is detected meters before it enters the region, while being inside, and until moving several meters away. On the other hand, when counters are used individually or in pairs, the source is detected for much shorter durations, and sometimes not detected at all while inside the region.

Original language	English
Pages (from-to)	326-331
Number of pages	6
Journal	Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
Volume	784
DOIs	https://doi.org/10.1016/j.nima.2015.01.037
State	Published - Jun 1 2015

Funding

This work has been supported by the U.S. Department of Homeland Security, Domestic Nuclear Detection Office, under competitively awarded contract No. IAA HSHQDC-13-X-B0002. This support does not constitute an expressed or implied endorsement on the part of the Government.

Keywords

Border monitoring
Detection networks
Particle filters

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10.1016/j.nima.2015.01.037

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Rao, N. S. V., Sen, S., Prins, N. J., Cooper, D. A., Ledoux, R. J., Costales, J. B., Kamieniecki, K., Korbly, S. E., Thompson, J. K., Batcheler, J., Brooks, R. R., & Wu, C. Q. (2015). Network algorithms for detection of radiation sources. Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 784, 326-331. https://doi.org/10.1016/j.nima.2015.01.037

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title = "Network algorithms for detection of radiation sources",

abstract = "Networks of radiation counters have been recently developed for detecting low-level, hazardous radiation sources, and they have been utilized in indoor and outdoor characterization tests. Subsequently, the test measurements have been {"}replayed{"} using multiple sub-networks, which enabled the analysis of various scenarios beyond the tests. We present a particle filter algorithm that combines measurements from gamma counters across the network to detect radiation sources. Using replays from an outdoor test, we construct a border monitoring scenario that consists of twelve 2 in.×2 in. NaI detectors or counters deployed on the periphery to monitor a 42×42 m2 region. A 137Cs source is moved across this region, starting several meters outside and finally moving away from it. The measurements from individual, pairs and boundary detectors are replayed using the particle filter algorithm. The algorithm outputs demonstrate, both quantitatively and qualitatively, the benefits of networking all boundary counters: the source is detected meters before it enters the region, while being inside, and until moving several meters away. On the other hand, when counters are used individually or in pairs, the source is detected for much shorter durations, and sometimes not detected at all while inside the region.",

keywords = "Border monitoring, Detection networks, Particle filters",

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Rao, NSV, Sen, S, Prins, NJ, Cooper, DA, Ledoux, RJ, Costales, JB, Kamieniecki, K, Korbly, SE, Thompson, JK, Batcheler, J, Brooks, RR & Wu, CQ 2015, 'Network algorithms for detection of radiation sources', Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, vol. 784, pp. 326-331. https://doi.org/10.1016/j.nima.2015.01.037

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T1 - Network algorithms for detection of radiation sources

AU - Rao, Nageswara S.V.

AU - Sen, Satyabrata

AU - Prins, Nicholas J.

AU - Cooper, Daniel A.

AU - Ledoux, Robert J.

AU - Costales, James B.

AU - Kamieniecki, Krzysztof

AU - Korbly, Steven E.

AU - Thompson, Jeffrey K.

AU - Batcheler, James

AU - Brooks, Richard R.

AU - Wu, Chase Q.

PY - 2015/6/1

Y1 - 2015/6/1

N2 - Networks of radiation counters have been recently developed for detecting low-level, hazardous radiation sources, and they have been utilized in indoor and outdoor characterization tests. Subsequently, the test measurements have been "replayed" using multiple sub-networks, which enabled the analysis of various scenarios beyond the tests. We present a particle filter algorithm that combines measurements from gamma counters across the network to detect radiation sources. Using replays from an outdoor test, we construct a border monitoring scenario that consists of twelve 2 in.×2 in. NaI detectors or counters deployed on the periphery to monitor a 42×42 m2 region. A 137Cs source is moved across this region, starting several meters outside and finally moving away from it. The measurements from individual, pairs and boundary detectors are replayed using the particle filter algorithm. The algorithm outputs demonstrate, both quantitatively and qualitatively, the benefits of networking all boundary counters: the source is detected meters before it enters the region, while being inside, and until moving several meters away. On the other hand, when counters are used individually or in pairs, the source is detected for much shorter durations, and sometimes not detected at all while inside the region.

AB - Networks of radiation counters have been recently developed for detecting low-level, hazardous radiation sources, and they have been utilized in indoor and outdoor characterization tests. Subsequently, the test measurements have been "replayed" using multiple sub-networks, which enabled the analysis of various scenarios beyond the tests. We present a particle filter algorithm that combines measurements from gamma counters across the network to detect radiation sources. Using replays from an outdoor test, we construct a border monitoring scenario that consists of twelve 2 in.×2 in. NaI detectors or counters deployed on the periphery to monitor a 42×42 m2 region. A 137Cs source is moved across this region, starting several meters outside and finally moving away from it. The measurements from individual, pairs and boundary detectors are replayed using the particle filter algorithm. The algorithm outputs demonstrate, both quantitatively and qualitatively, the benefits of networking all boundary counters: the source is detected meters before it enters the region, while being inside, and until moving several meters away. On the other hand, when counters are used individually or in pairs, the source is detected for much shorter durations, and sometimes not detected at all while inside the region.

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KW - Detection networks

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JF - Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment

ER -

Network algorithms for detection of radiation sources

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