research-article

Identification of low-level point radioactive sources using a sensor network

Authors:

Jren-Chit Chin,

Nageswara S. V. Rao,

David K. Y. Yau,

Mallikarjun Shankar,

Jennifer C. Hou,

Srinivasagopalan Srivathsan,

Sitharama IyengarAuthors Info & Claims

ACM Transactions on Sensor Networks (TOSN), Volume 7, Issue 3

Article No.: 21, Pages 1 - 35

https://doi.org/10.1145/1807048.1807050

Published: 04 October 2010 Publication History

Abstract

Identification of a low-level point radioactive source amidst background radiation is achieved by a network of radiation sensors using a two-step approach. Based on measurements from three or more sensors, a geometric difference triangulation method or an N-sensor localization method is used to estimate the location and strength of the source. Then a sequential probability ratio test based on current measurements and estimated parameters is employed to finally decide: (1) the presence of a source with the estimated parameters, or (2) the absence of the source, or (3) the insufficiency of measurements to make a decision. This method achieves specified levels of false alarm and missed detection probabilities, while ensuring a close-to-minimal number of measurements for reaching a decision. This method minimizes the ghost-source problem of current estimation methods, and achieves a lower false alarm rate compared with current detection methods. This method is tested and demonstrated using: (1) simulations, and (2) a test-bed that utilizes the scaling properties of point radioactive sources to emulate high intensity ones that cannot be easily and safely handled in laboratory experiments.

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Index Terms

Identification of low-level point radioactive sources using a sensor network
1. Networks
  1. Network architectures

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Published In

cover image ACM Transactions on Sensor Networks

ACM Transactions on Sensor Networks Volume 7, Issue 3

September 2010

220 pages

ISSN:1550-4859

EISSN:1550-4867

DOI:10.1145/1807048

Issue’s Table of Contents

Copyright © 2010 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 04 October 2010

Accepted: 01 April 2010

Revised: 01 October 2009

Received: 01 February 2009

Published in TOSN Volume 7, Issue 3

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Cited By

Bandstra MHellfeld DLee JQuiter BSalathe MVavrek JJoshi T(2023)Mapping the Minimum Detectable Activities of Gamma-Ray Sources in a 3-D SceneIEEE Transactions on Nuclear Science10.1109/TNS.2022.322670770:1(64-75)Online publication date: Jan-2023
https://doi.org/10.1109/TNS.2022.3226707
Abdelhakim A(2023)Heuristic techniques for maximum likelihood localization of radioactive sources via a sensor networkNuclear Science and Techniques10.1007/s41365-023-01267-334:8Online publication date: 28-Aug-2023
https://doi.org/10.1007/s41365-023-01267-3
Xiang CYang PXiao FFan XXiang CYang PXiao FFan X(2023)Environmental Protection Application: Urban Pollution MonitoringMulti-dimensional Urban Sensing Using Crowdsensing Data10.1007/978-981-19-9006-9_4(95-111)Online publication date: 24-Mar-2023
https://doi.org/10.1007/978-981-19-9006-9_4
Mahmoud IAbd el-Hamid A(2022)Particle Filter Based Range Search Approach for Localization of Radioactive MaterialsFrontiers in Energy Research10.3389/fenrg.2021.8079189Online publication date: 31-Jan-2022
https://doi.org/10.3389/fenrg.2021.807918
Parrilla HAger DBandstra MBerwick DCooper RFolsom MKeydel EMorgan AMosher BNegut V(2022)Enhancing 3D Gamma-Ray Imaging with Through-Wall Radar2022 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)10.1109/NSS/MIC44845.2022.10399009(1-7)Online publication date: 5-Nov-2022
https://doi.org/10.1109/NSS/MIC44845.2022.10399009
Liu YXuan YZhang DZou S(2022)Localizing unknown radiation sources by unscented particle filtering based on divide-and-conquer samplingJournal of Nuclear Science and Technology10.1080/00223131.2022.203285859:9(1149-1161)Online publication date: 3-Mar-2022
https://doi.org/10.1080/00223131.2022.2032858
Bandstra MHellfeld DVavrek JQuiter BMeehan KBarton PCates JMoran ANegut VPavlovsky RJoshi T(2021)Improved Gamma-Ray Point Source Quantification in Three Dimensions by Modeling Attenuation in the SceneIEEE Transactions on Nuclear Science10.1109/TNS.2021.311358868:11(2637-2646)Online publication date: Nov-2021
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Xiang CFan XChen CGong LGuo S(2021)Fisher information-empowered sensing quality quantification for crowdsensing networksNeural Computing and Applications10.1007/s00521-020-05501-633:13(7563-7574)Online publication date: 1-Jul-2021
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Meghanathan N(2020)Eigenvector Centrality-Based Mobile Target Tracking in Wireless Sensor NetworksSensor Technology10.4018/978-1-7998-2454-1.ch054(1150-1167)Online publication date: 2020
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Yadav IEckenhoff KHuang GTanner H(2020)Motion Planning and Visual-Inertial Target Tracking for UAV-based Radiation Detection2020 28th Mediterranean Conference on Control and Automation (MED)10.1109/MED48518.2020.9183297(1009-1014)Online publication date: Sep-2020
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