An Innovative Radiation Source Localization Algorithm By Bayesian Theory Based on Electromagnetic Map

Using electromagnetic maps to locate radiation sources can achieve spectrum analysis and management of target areas, optimized allocation of communication resources, and optimized network design, thereby reducing the waste of spectrum resources, communication resources, and network resources, and achieving the goal of green communication. This article studies an innovative electromagnetic map supported radiation source localization algorithm based on Bayesian theorem. Firstly, the Kriging interpolation method is used to reconstruct the electromagnetic map of the target area. Then, the key areas of the radiation source position and the distribution probability of the radiation source are determined based on the reconstructed electromagnetic map. The movable sensing nodes are used to observe the key areas and construct a likelihood function. Finally, the Bayesian theorem is used to combine the likelihood function with the distribution probability to obtain the updated distribution probability of the radiation source position, thereby achieving inference of the radiation source position. The effectiveness and progressiveness of the algorithm are verified by experimental simulation and comparison.

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Publication Details

Published
2024-10-18
DOI
https://doi.org/10.1109/icct62411.2024.10946550
Primary Topic
Optical Systems and Laser Technology
Type
article
Field-Weighted Citation Impact
0.00

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article

An Innovative Radiation Source Localization Algorithm By Bayesian Theory Based on Electromagnetic Map

Hongjun Wang, Zhexian Shen, Haojin Li, Yixiao Zhang
Optical Systems and Laser Technology
article

An Innovative Radiation Source Localization Algorithm By Bayesian Theory Based on Electromagnetic Map

Hongjun Wang, Zhexian Shen, Haojin Li, Yixiao Zhang
article en

Abstract

Using electromagnetic maps to locate radiation sources can achieve spectrum analysis and management of target areas, optimized allocation of communication resources, and optimized network design, thereby reducing the waste of spectrum resources, communication resources, and network resources, and achieving the goal of green communication. This article studies an innovative electromagnetic map supported radiation source localization algorithm based on Bayesian theorem. Firstly, the Kriging interpolation method is used to reconstruct the electromagnetic map of the target area. Then, the key areas of the radiation source position and the distribution probability of the radiation source are determined based on the reconstructed electromagnetic map. The movable sensing nodes are used to observe the key areas and construct a likelihood function. Finally, the Bayesian theorem is used to combine the likelihood function with the distribution probability to obtain the updated distribution probability of the radiation source position, thereby achieving inference of the radiation source position. The effectiveness and progressiveness of the algorithm are verified by experimental simulation and comparison.

National University of Defense Technology (CN)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 73%
Optical Systems and Laser Technology
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