A source-attractor approach to network detection of radiation sources

Chase Q. Wu, Mark L. Berry, Kayla M. Grieme, Satyabrata Sen, Nageswara S.V. Rao, Richard R. Brooks, Guthrie Cordone

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Radiation source detection using a network of detectors is an active field of research for homeland security and defense applications. We propose Source-attractor Radiation Detection (SRD) method to aggregate measurements from a network of detectors for radiation source detection. SRD method models a potential radiation source as a 'magnet'-like attractor that pulls in pre-computed virtual points from the detector locations. A detection decision is made if a sufficient level of attraction, quantified by the increase in the clustering of the shifted virtual points, is observed. Compared with traditional methods, SRD has the following advantages: i) it does not require an accurate estimate of the source location from limited and noise-corrupted sensor readings, unlike the localization-based methods, and ii) its virtual point shifting and clustering calculation involve simple arithmetic operations based on the number of detectors, avoiding the high computational complexity of grid-based likelihood estimation methods. We evaluate its detection performance using canonical datasets from Domestic Nuclear Detection Office's (DNDO) Intelligence Radiation Sensors Systems (IRSS) tests. SRD achieves both lower false alarm rate and false negative rate compared to three existing algorithms for network source detection.

Original languageEnglish (US)
Title of host publication2016 IEEE lnternational Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages394-399
Number of pages6
ISBN (Electronic)9781467397087
DOIs
StatePublished - Jul 2 2016
Event2016 IEEE lnternational Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2016 - Baden-Baden, Germany
Duration: Sep 19 2016Sep 21 2016

Publication series

NameIEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems
Volume0

Other

Other2016 IEEE lnternational Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2016
CountryGermany
CityBaden-Baden
Period9/19/169/21/16

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Computer Science Applications

Keywords

  • Radiation detection
  • object localization
  • sensor networks

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