无线传感器网络中基于传感器选择的声源定位

Y. Feng, Guohua Hu, Lei Hong
{"title":"无线传感器网络中基于传感器选择的声源定位","authors":"Y. Feng, Guohua Hu, Lei Hong","doi":"10.1145/3446132.3446419","DOIUrl":null,"url":null,"abstract":"Since the bandwidth and energy of wireless sensor networks (WSNs) are limited, it is not appropriate to use all the sensors for acoustic source positioning and so the need for sensor selection. In the article, an efficient expectation maximization algorithm based on sensor selection (EM-SS) is proposed for acoustic source positioning in the WSNs. The sensor selection solution based on the generalized information gain is introduced to select a subset of sensors which can provide reliable measurements. The information filter only depends on the Boolean decision variables and may make full use of the structure of measurement noise. Fewer sensor nodes are used and mass energy is economized. Simulation results demonstrate the well performance of the EM-SS algorithm in terms of localization accuracy, while only a part of sensors is used, so mass energy is economized and the communication channel is smooth.","PeriodicalId":125388,"journal":{"name":"Proceedings of the 2020 3rd International Conference on Algorithms, Computing and Artificial Intelligence","volume":"73 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Acoustic Source Positioning based on Sensor Selection in Wireless Sensor Network\",\"authors\":\"Y. Feng, Guohua Hu, Lei Hong\",\"doi\":\"10.1145/3446132.3446419\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Since the bandwidth and energy of wireless sensor networks (WSNs) are limited, it is not appropriate to use all the sensors for acoustic source positioning and so the need for sensor selection. In the article, an efficient expectation maximization algorithm based on sensor selection (EM-SS) is proposed for acoustic source positioning in the WSNs. The sensor selection solution based on the generalized information gain is introduced to select a subset of sensors which can provide reliable measurements. The information filter only depends on the Boolean decision variables and may make full use of the structure of measurement noise. Fewer sensor nodes are used and mass energy is economized. Simulation results demonstrate the well performance of the EM-SS algorithm in terms of localization accuracy, while only a part of sensors is used, so mass energy is economized and the communication channel is smooth.\",\"PeriodicalId\":125388,\"journal\":{\"name\":\"Proceedings of the 2020 3rd International Conference on Algorithms, Computing and Artificial Intelligence\",\"volume\":\"73 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2020 3rd International Conference on Algorithms, Computing and Artificial Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3446132.3446419\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2020 3rd International Conference on Algorithms, Computing and Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3446132.3446419","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

由于无线传感器网络的带宽和能量有限,不适合使用所有传感器进行声源定位,因此需要对传感器进行选择。本文提出了一种基于传感器选择的有效期望最大化算法(EM-SS),用于WSNs中的声源定位。介绍了基于广义信息增益的传感器选择方法,以选择能够提供可靠测量的传感器子集。信息滤波只依赖于布尔决策变量,可以充分利用测量噪声的结构。使用较少的传感器节点,节约了大量的能量。仿真结果表明,EM-SS算法在定位精度方面具有良好的性能,且只使用了一部分传感器,节省了大量能量,通信通道畅通。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Acoustic Source Positioning based on Sensor Selection in Wireless Sensor Network
Since the bandwidth and energy of wireless sensor networks (WSNs) are limited, it is not appropriate to use all the sensors for acoustic source positioning and so the need for sensor selection. In the article, an efficient expectation maximization algorithm based on sensor selection (EM-SS) is proposed for acoustic source positioning in the WSNs. The sensor selection solution based on the generalized information gain is introduced to select a subset of sensors which can provide reliable measurements. The information filter only depends on the Boolean decision variables and may make full use of the structure of measurement noise. Fewer sensor nodes are used and mass energy is economized. Simulation results demonstrate the well performance of the EM-SS algorithm in terms of localization accuracy, while only a part of sensors is used, so mass energy is economized and the communication channel is smooth.
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