一种基于 WiFi 的新型时态精确检测系统,具有增强型 CSI 采样功能

IF 4.6 3区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Jin Huang;Yue Tian;Xuejie Hu;Zhidu Li
{"title":"一种基于 WiFi 的新型时态精确检测系统,具有增强型 CSI 采样功能","authors":"Jin Huang;Yue Tian;Xuejie Hu;Zhidu Li","doi":"10.1109/LWC.2024.3490663","DOIUrl":null,"url":null,"abstract":"Integrated sensing and communication (ISAC) has emerged as a prominent research focus in the domains of 5G-Advanced (5G-A), 6G, and wireless fidelity (WiFi). As a passive sensing technology, WiFi-based human detection has garnered widespread attention due to its privacy, unobtrusiveness, and convenience in practical applications. This letter introduces a WiFi-based human intrusion detection system utilizing channel state information (CSI). By refining the CSI phase sampling points through the proposed sequence particle filter (SPF) CSI sampling method, the system reduces the amount of data needed for real-time sensing. A comprehensive preprocessing procedure is presented to filter out noise interference and mitigate channel fading during CSI collection. The proposed human intrusion detection algorithm accurately identifies fluctuations in the CSI phase time series, thereby determining the presence of a human and the exact moments of intrusion.","PeriodicalId":13343,"journal":{"name":"IEEE Wireless Communications Letters","volume":"14 1","pages":"128-132"},"PeriodicalIF":4.6000,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Novel WiFi-Based Temporal Precision Detection System With Enhanced CSI Sampling\",\"authors\":\"Jin Huang;Yue Tian;Xuejie Hu;Zhidu Li\",\"doi\":\"10.1109/LWC.2024.3490663\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Integrated sensing and communication (ISAC) has emerged as a prominent research focus in the domains of 5G-Advanced (5G-A), 6G, and wireless fidelity (WiFi). As a passive sensing technology, WiFi-based human detection has garnered widespread attention due to its privacy, unobtrusiveness, and convenience in practical applications. This letter introduces a WiFi-based human intrusion detection system utilizing channel state information (CSI). By refining the CSI phase sampling points through the proposed sequence particle filter (SPF) CSI sampling method, the system reduces the amount of data needed for real-time sensing. A comprehensive preprocessing procedure is presented to filter out noise interference and mitigate channel fading during CSI collection. The proposed human intrusion detection algorithm accurately identifies fluctuations in the CSI phase time series, thereby determining the presence of a human and the exact moments of intrusion.\",\"PeriodicalId\":13343,\"journal\":{\"name\":\"IEEE Wireless Communications Letters\",\"volume\":\"14 1\",\"pages\":\"128-132\"},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2024-11-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Wireless Communications Letters\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10742082/\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Wireless Communications Letters","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10742082/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0

摘要

集成传感和通信(ISAC)已成为5G-Advanced (5G-A), 6G和无线保真(WiFi)领域的突出研究焦点。基于wifi的人体检测作为一种被动传感技术,在实际应用中因其私密性、不显眼性和便捷性而受到广泛关注。本文介绍了一种利用信道状态信息(CSI)的基于wifi的人类入侵检测系统。通过提出的序列粒子滤波(SPF) CSI采样方法对CSI相位采样点进行细化,减少了实时传感所需的数据量。提出了一种综合的预处理方法,以滤除CSI采集过程中的噪声干扰和减轻信道衰落。本文提出的人类入侵检测算法可以准确识别CSI相位时间序列的波动,从而确定人类的存在和入侵的准确时刻。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Novel WiFi-Based Temporal Precision Detection System With Enhanced CSI Sampling
Integrated sensing and communication (ISAC) has emerged as a prominent research focus in the domains of 5G-Advanced (5G-A), 6G, and wireless fidelity (WiFi). As a passive sensing technology, WiFi-based human detection has garnered widespread attention due to its privacy, unobtrusiveness, and convenience in practical applications. This letter introduces a WiFi-based human intrusion detection system utilizing channel state information (CSI). By refining the CSI phase sampling points through the proposed sequence particle filter (SPF) CSI sampling method, the system reduces the amount of data needed for real-time sensing. A comprehensive preprocessing procedure is presented to filter out noise interference and mitigate channel fading during CSI collection. The proposed human intrusion detection algorithm accurately identifies fluctuations in the CSI phase time series, thereby determining the presence of a human and the exact moments of intrusion.
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
IEEE Wireless Communications Letters
IEEE Wireless Communications Letters Engineering-Electrical and Electronic Engineering
CiteScore
12.30
自引率
6.30%
发文量
481
期刊介绍: IEEE Wireless Communications Letters publishes short papers in a rapid publication cycle on advances in the state-of-the-art of wireless communications. Both theoretical contributions (including new techniques, concepts, and analyses) and practical contributions (including system experiments and prototypes, and new applications) are encouraged. This journal focuses on the physical layer and the link layer of wireless communication systems.
×
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