Heuristic techniques for maximum likelihood localization of radioactive sources via a sensor network

Assem Abdelhakim

doi:10.1007/s41365-023-01267-3

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Heuristic techniques for maximum likelihood localization of radioactive sources via a sensor network

NUCLEAR PHYSICS AND INTERDISCIPLINARY RESEARCH | Updated：2023-09-19

- Heuristic techniques for maximum likelihood localization of radioactive sources via a sensor network
- Heuristic techniques for maximum likelihood localization of radioactive sources via a sensor network
- 核技术（英文版） 2023年34卷第8期文章编号：127
- Affiliations：
  
  1.Department of Radiation Engineering, National Center for Radiation Research and Technology, Egyptian Atomic Energy Authority, 11787, Cairo, Egypt.
- Author bio：
  
  assem.abdelhakim@eaea.org.eg
- Funds：
- DOI：10.1007/s41365-023-01267-3
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Heuristic techniques for maximum likelihood localization of radioactive sources via a sensor network[J]. 核技术（英文版）, 2023,34(8):127

Assem Abdelhakim. Heuristic techniques for maximum likelihood localization of radioactive sources via a sensor network[J]. Nuclear Science and Techniques, 2023,34(8):127
Heuristic techniques for maximum likelihood localization of radioactive sources via a sensor network[J]. 核技术（英文版）, 2023,34(8):127 DOI： 10.1007/s41365-023-01267-3.

Assem Abdelhakim. Heuristic techniques for maximum likelihood localization of radioactive sources via a sensor network[J]. Nuclear Science and Techniques, 2023,34(8):127 DOI： 10.1007/s41365-023-01267-3.

摘要

Abstract

Maximum likelihood estimation (MLE) is an effective method for localizing radioactive sources in a given area. However, it requires an exhaustive search for parameter estimation, which is time consuming. In this study, heuristic techniques were employed to search for radiation source parameters that provide the maximum likelihood by using a network of sensors. Hence, the time consumption of MLE would be effectively reduced. First, the radiation source was detected using the ,k,-sigma method. Subsequently, the MLE was applied for parameter estimation using the readings and positions of the detectors that have detected the radiation source. A comparative study was performed in which the estimation accuracy and time consumption of the MLE were evaluated for traditional methods and heuristic techniques. The traditional MLE was performed via a grid search method using fixed and multiple resolutions. Additionally, four commonly used heuristic algorithms were applied: the firefly algorithm (FFA), particle swarm optimization (PSO), ant colony optimization (ACO), and artificial bee colony (ABC). The experiment was conducted using real data collected by the Low Scatter Irradiator facility at the Savannah River National Laboratory as part of the Intelligent Radiation Sensing System program. The comparative study showed that the estimation time was 3.27 s using fixed resolution MLE and 0.59 s using multi-resolution MLE. The time consumption for the heuristic-based MLE was 0.75, 0.03, 0.02, and 0.059 s for FFA, PSO, ACO, and ABC, respectively. The location estimation error was approximately 0.4 m using either the grid search-based MLE or the heuristic-based MLE. Hence, heuristic-based MLE can provide comparable estimation accuracy through a less time consuming process than traditional MLE

关键词

Keywords

Radioactive sourceMaximum Likelihood Estimation Multi-resolution MLEk-sigmaFirefly algorithmParticle swarm optimizationAnt colony optimizationArtificial bee colony

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