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基于自适应M-H采样的放射源定位算法
Radioactive Source Localization Algorithm Based on Adaptive M-H Sampling
【摘要】 针对放射源定位中的仪器设施昂贵且定位过程复杂的问题,提出了一种自适应M-H采样的放射源定位算法。利用轻便的个人剂量仪获取辐射场内不同测量点的剂量;再根据放射源的空间衰变规律,建立点放射源位置估计的贝叶斯推理模型,得到放射源参数的后验分布;通过自适应调整初始值和提议函数方差的M-H算法对后验分布进行采样,实现了室内环境中点放射源的定位。采用Eu-152展开实验,实验结果表明:提出的算法能够以较小的误差定位裸源,方法可行、有效。
【Abstract】 In order to solve the problem of expensive instrumentation and complicated positioning process in locating radioactive sources,a self-adaptive M-H sampling algorithm for locating the radioactive sources is proposed. Firstly,the dose of different measurement points in the radiation field was obtained by a portable personal dosimeter.Then, based on the spatial decay law of the source,a Bayesian inference model for estimating the position of the point source was established, and the posterior distribution of the source parameters was obtained. Finally,the posterior distribution was sampled by the M-H algorithm which adaptively adjusts the initial value and the proposed function variance to realize the localization of the point source in the indoor environment.The experiments were carried out with Eu-152.The experimental results show that the proposed algorithm can locate the bare source with a small error,and the method is feasible and effective.
【Key words】 radiation source localization; Bayesian inference; MCMC; Metropolis-Hastings algorithm; parameter estimation;
- 【文献出处】 测控技术 ,Measurement & Control Technology , 编辑部邮箱 ,2019年06期
- 【分类号】X837
- 【网络出版时间】2019-01-10 16:51
- 【被引频次】7
- 【下载频次】219