信息增益驱动的放射性点源搜索

B. Ristic, A. Gunatilaka, M. Rutten
{"title":"信息增益驱动的放射性点源搜索","authors":"B. Ristic, A. Gunatilaka, M. Rutten","doi":"10.1109/ICIF.2007.4408041","DOIUrl":null,"url":null,"abstract":"The paper presents an algorithm for detection and a subsequent information gain driven search for an unaccounted point source of relatively low-level gamma radiation. Source detection and parameter estimation are carried out jointly in the Bayesian framework using a particle filter. The observer control vector consists of the next sensor location and the exposure time. During the pre-detection search, the control vectors take predefined values. After detection, the optimal control vector is selected via a multiple-step ahead maximisation of the Fisher information gain.","PeriodicalId":298941,"journal":{"name":"2007 10th International Conference on Information Fusion","volume":"298 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"An information gain driven search for a radioactive point source\",\"authors\":\"B. Ristic, A. Gunatilaka, M. Rutten\",\"doi\":\"10.1109/ICIF.2007.4408041\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper presents an algorithm for detection and a subsequent information gain driven search for an unaccounted point source of relatively low-level gamma radiation. Source detection and parameter estimation are carried out jointly in the Bayesian framework using a particle filter. The observer control vector consists of the next sensor location and the exposure time. During the pre-detection search, the control vectors take predefined values. After detection, the optimal control vector is selected via a multiple-step ahead maximisation of the Fisher information gain.\",\"PeriodicalId\":298941,\"journal\":{\"name\":\"2007 10th International Conference on Information Fusion\",\"volume\":\"298 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-07-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 10th International Conference on Information Fusion\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIF.2007.4408041\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 10th International Conference on Information Fusion","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIF.2007.4408041","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 16

摘要

本文提出了一种算法,用于检测和随后的信息增益驱动搜索相对低水平伽马辐射的不明点源。利用粒子滤波在贝叶斯框架下进行源检测和参数估计。观测器控制向量由下一个传感器位置和曝光时间组成。在预检测搜索过程中,控制向量取预定义值。检测后,通过对费雪信息增益的多步最大化来选择最优控制向量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An information gain driven search for a radioactive point source
The paper presents an algorithm for detection and a subsequent information gain driven search for an unaccounted point source of relatively low-level gamma radiation. Source detection and parameter estimation are carried out jointly in the Bayesian framework using a particle filter. The observer control vector consists of the next sensor location and the exposure time. During the pre-detection search, the control vectors take predefined values. After detection, the optimal control vector is selected via a multiple-step ahead maximisation of the Fisher information gain.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信