基于无线传感器网络的多目标声分类与跟踪

Joonghyun Lee, H. Kim
{"title":"基于无线传感器网络的多目标声分类与跟踪","authors":"Joonghyun Lee, H. Kim","doi":"10.1109/ICCAS.2015.7364947","DOIUrl":null,"url":null,"abstract":"This paper presents an acoustic classification and multi-sensor tracking algorithm with WSNs for multiple targets. The goal for this study is to classify the targets and identify the traces of moving multiple targets with their acoustic characteristics and received signal strength indicator. The paper describes a distinctive method to select features from the raw acoustic signal which contains both time and frequency domain information. For trace identification, the method for labeling unidentified traces with appropriate target is introduced. By using the suggested algorithm, the classifier shows more accurate and faster responding performance than the classifiers which use only frequency domain input. Experimental results show the satisfactory performance of the proposed algorithm.","PeriodicalId":6641,"journal":{"name":"2015 15th International Conference on Control, Automation and Systems (ICCAS)","volume":"130 1","pages":"399-404"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Acoustic classification and tracking of multiple targets using wireless sensor networks\",\"authors\":\"Joonghyun Lee, H. Kim\",\"doi\":\"10.1109/ICCAS.2015.7364947\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an acoustic classification and multi-sensor tracking algorithm with WSNs for multiple targets. The goal for this study is to classify the targets and identify the traces of moving multiple targets with their acoustic characteristics and received signal strength indicator. The paper describes a distinctive method to select features from the raw acoustic signal which contains both time and frequency domain information. For trace identification, the method for labeling unidentified traces with appropriate target is introduced. By using the suggested algorithm, the classifier shows more accurate and faster responding performance than the classifiers which use only frequency domain input. Experimental results show the satisfactory performance of the proposed algorithm.\",\"PeriodicalId\":6641,\"journal\":{\"name\":\"2015 15th International Conference on Control, Automation and Systems (ICCAS)\",\"volume\":\"130 1\",\"pages\":\"399-404\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-12-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 15th International Conference on Control, Automation and Systems (ICCAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCAS.2015.7364947\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 15th International Conference on Control, Automation and Systems (ICCAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCAS.2015.7364947","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

提出了一种基于WSNs的多目标声分类和多传感器跟踪算法。本研究的目的是利用目标的声学特征和接收信号强度指标对目标进行分类,识别多目标的运动轨迹。本文提出了一种从包含时域和频域信息的原始声信号中提取特征的独特方法。在迹迹识别方面,介绍了用合适的目标标记未识别迹迹的方法。与仅使用频域输入的分类器相比,该分类器具有更高的准确率和更快的响应性能。实验结果表明,该算法具有良好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Acoustic classification and tracking of multiple targets using wireless sensor networks
This paper presents an acoustic classification and multi-sensor tracking algorithm with WSNs for multiple targets. The goal for this study is to classify the targets and identify the traces of moving multiple targets with their acoustic characteristics and received signal strength indicator. The paper describes a distinctive method to select features from the raw acoustic signal which contains both time and frequency domain information. For trace identification, the method for labeling unidentified traces with appropriate target is introduced. By using the suggested algorithm, the classifier shows more accurate and faster responding performance than the classifiers which use only frequency domain input. Experimental results show the satisfactory performance of the proposed algorithm.
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
期刊最新文献
Backstepping and backstepping sliding mode controller for droplet position in electrowetting on Dielectric system Procurement scheduling under supply and demand uncertainty: Case study for comparing classical, reactive, and proactive scheduling Design of an assistance robot for patients suffering from Paraplegia A reel-time control for precise walking of bipped robot Fabrication of 3D printed circuit device by using direct write technology
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1