Journal of Nuclear Science, Engineering and Technology (JONSAT)
In cooperation with the Iranian Nuclear Society

Detection and localization of mobile and weak radioactive sources by data-fusion of a surveillance camera and a NaI detector in the continuous and discontinuous modes

Document Type : Research Paper

Authors

H. Ardiny
M. Askari
A.M. Beigzadeh

Radiation Applications Research School, Nuclear Science and Technology Research Institute, AEOI, P.O.Box: 1339-14155, Tehran-Iran

https://doi.org/10.24200/nst.2022.1451
Abstract
Although nuclear energy and radioactive materials have considerably impressed national health and economics, inappropriate use of radioactive materials can pose a significant threat to public health and security. This research aims to enhance defensive capabilities for countering nuclear terrorism by accurate detection and continuous tracking. A vital component of this system is to equip surveillance cameras of a region with a relatively low-cost radiation detector (NaI detectors) for counting gamma rays. Data-fusion of the surveillance camera and radioactive sensor that is linked together helps us detect and localize suspicious sources among other objects. The system can provide data flow (continuous) or a collection of snapshots several times (discontinuous), then a fast and new algorithm detects the suspicious source in these two modes. The promising results represent the integrated system by employing the new algorithm to detect the suspicious source in both data modes. Still, the source can be detected quicker in the continuous mode.

Highlights

1.             B.D. Geelhood, et al, Overview of portal monitoring at border crossings, IEEE Nucl. Sci. Symp. Conf. Rec., Institute of Electrical and Electronics Engineers Inc., 513 (2003).

 

2.             A. Farzanehpoor Alwars, F. Rahmani, A feasibility study of gamma ray source finder development for multiple sources scenario based on a Monte Carlo simulation, Sci. Rep., 11(1), 6121 (2021).

 

3. J.V. Candy, Detection Classification and Estimation of Radioactive Contraband from Uncertain Low-Count Measurements, Tech rep., CA United States, (2010).

 

4. W. Cruz, Characterization of radioactive orphan sources by gamma spectrometry, Regional Congress of IRPA on Radiological and Nuclear Safety, (Brazil 2013).

 

5. A.H.-W. Liu, M.Sc. thesis, California Institute of Technology, (2010).

 

6.             P. Tandon, et al., Detection of radioactive sources in urban scenes using Bayesian Aggregation of data from mobile spectrometers, Information Systems, 57, 195-206 (2016).

 

7. J. Zhao, M.Sc. thesis, University of Illinois, (2016).

 

8. P.G. Martin, et al., 3D unmanned aerial vehicle radiation mapping for assessing contaminant distribution and mobility, Int. J. Appl. Earth Obs. Geoinf., 52, 12 (2016).

 

9. S.M. Brennan, et al., Radiation detection with distributed sensor networks, Computer (Long. Beach. Calif, 2004)., 37(8), 57–59 (2004).

 

10. K. Stadnikia, et al., Data fusion for a vision-aided radiological detection system: Correlation methods for single source tracking, Nucl. Instruments Methods Phys. Res. Sect. A Accel. Spectrometers, Detect. Assoc. Equip., 954, 161913 (2020).

 

11. K. Stadnikia, et al., Data fusion for a vision-aided radiological detection system: Calibration algorithm performance, Nucl. Instruments Methods Phys. Res. Sect. A Accel. Spectrometers, Detect. Assoc. Equip., 890, 8 (2018).

 

12. N. Van Thai, L.C. Chen, In-situ indoor 3-D land mapping and radioactive source localization, 2013 IEEE/ASME Int. Conf. Adv. Intell. Mechatronics Mechatronics (Hum. Wellbeing, 2013), 1404–1409.

 

13. F. Mondada, et al., Bringing Robotics to Formal Education: The Thymio Open-Source Hardware Robot, IEEE Robot. Autom. Mag., 24(1), 77 (2017).

Keywords

Data-fusion
Detection
Localization
Mobile sources
Material out of regulatory control
1.             B.D. Geelhood, et al, Overview of portal monitoring at border crossings, IEEE Nucl. Sci. Symp. Conf. Rec., Institute of Electrical and Electronics Engineers Inc., 513 (2003).
 
2.             A. Farzanehpoor Alwars, F. Rahmani, A feasibility study of gamma ray source finder development for multiple sources scenario based on a Monte Carlo simulation, Sci. Rep., 11(1), 6121 (2021).
 
3. J.V. Candy, Detection Classification and Estimation of Radioactive Contraband from Uncertain Low-Count Measurements, Tech rep., CA United States, (2010).
 
4. W. Cruz, Characterization of radioactive orphan sources by gamma spectrometry, Regional Congress of IRPA on Radiological and Nuclear Safety, (Brazil 2013).
 
5. A.H.-W. Liu, M.Sc. thesis, California Institute of Technology, (2010).
 
6.             P. Tandon, et al., Detection of radioactive sources in urban scenes using Bayesian Aggregation of data from mobile spectrometers, Information Systems, 57, 195-206 (2016).
 
7. J. Zhao, M.Sc. thesis, University of Illinois, (2016).
 
8. P.G. Martin, et al., 3D unmanned aerial vehicle radiation mapping for assessing contaminant distribution and mobility, Int. J. Appl. Earth Obs. Geoinf., 52, 12 (2016).
 
9. S.M. Brennan, et al., Radiation detection with distributed sensor networks, Computer (Long. Beach. Calif, 2004)., 37(8), 57–59 (2004).
 
10. K. Stadnikia, et al., Data fusion for a vision-aided radiological detection system: Correlation methods for single source tracking, Nucl. Instruments Methods Phys. Res. Sect. A Accel. Spectrometers, Detect. Assoc. Equip., 954, 161913 (2020).
 
11. K. Stadnikia, et al., Data fusion for a vision-aided radiological detection system: Calibration algorithm performance, Nucl. Instruments Methods Phys. Res. Sect. A Accel. Spectrometers, Detect. Assoc. Equip., 890, 8 (2018).
 
12. N. Van Thai, L.C. Chen, In-situ indoor 3-D land mapping and radioactive source localization, 2013 IEEE/ASME Int. Conf. Adv. Intell. Mechatronics Mechatronics (Hum. Wellbeing, 2013), 1404–1409.
 
13. F. Mondada, et al., Bringing Robotics to Formal Education: The Thymio Open-Source Hardware Robot, IEEE Robot. Autom. Mag., 24(1), 77 (2017).

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