Detecting Low-level Radiation Sources Using Border Monitoring Gamma Sensors

Satyabrata Sen, Nageswara S.V. Rao, Chase Q. Wu, Richard R. Brooks, Christopher Temples

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

Abstract

We consider a problem of detecting a low-level radiation source using a network of Gamma spectral sensors placed on the periphery of a monitored region. We propose a computationally light-weight, correlation-based method which is primarily intended for systems with limited computing capacity. Sensor measurements are combined at the fusion by first generating decisions at each time step and then taking their majority vote within a time widow. At each time step, decisions are generated using two strategies: (i) SUM method based on a threshold decision on a correlation statistic derived from measurements from all sensors, and (ii) OR method based on logical-OR of threshold decisions based on correlations statistics of individual sensor measurements. We derive analytical performance bounds for false alarm rates of SUM and OR methods, and show that their performance is enhanced by the temporal smoothing of majority vote within a time window. Using measurements from a test campaign, we generate a border monitoring scenario with twelve 2"×2"NaI Gamma sensors deployed on the periphery of 42 × 42 m2 outdoor region. A Cs-137 source is moved in a straight-line across this region, starting several meters outside and finally moving away from it. We illustrate the performance of both correlation-based detection methods, and compare their performances with each other and with a particle filter method. Overall, under small false-alarm conditions, the OR fusion is found to produce better detection performance.

Original languageEnglish (US)
Title of host publication2020 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages342-347
Number of pages6
ISBN (Electronic)9781728164229
DOIs
StatePublished - Sep 14 2020
Externally publishedYes
Event2020 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2020 - Karlsruhe, Germany
Duration: Sep 14 2020Sep 16 2020

Publication series

NameIEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems
Volume2020-September

Conference

Conference2020 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2020
CountryGermany
CityKarlsruhe
Period9/14/209/16/20

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Computer Science Applications

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