{"title":"Decimeter-Level WiFi Tracking in Real-Time","authors":"Zheng Yang, Wei Gong","doi":"10.1109/IWQoS49365.2020.9212880","DOIUrl":null,"url":null,"abstract":"This paper presents DeTrack, a tracking system that can continuously trace WiFi objects at decimeter-level in real-time. To enable this, we make three main proposals. The first one is a super-resolution localization scheme that combines compressed sensing and expectation-maximization algorithms to iteratively resolve multi-path, which realizes better resolution compared against traditional MUSIC. The second one is a customized particle filter that takes advantage of WiFi signals and the geometric nature of AOA estimates to properly update location states and particle weights. Finally, an SVD-based multipacket fusion is employed to reinforce the signal space and improve tracking efficiency at the same time. A prototype is built using only commercial WiFi NICs. Extensive experiments demonstrate that DeTrack achieves an 80th percentile localization accuracy of 0.9 meters and a median latency of around 90 milliseconds. As a result, DeTrack is looking to benefit a wide range of applications, e.g., indoor navigation, intelligent logistics, and smart cities.","PeriodicalId":177899,"journal":{"name":"2020 IEEE/ACM 28th International Symposium on Quality of Service (IWQoS)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE/ACM 28th International Symposium on Quality of Service (IWQoS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWQoS49365.2020.9212880","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
This paper presents DeTrack, a tracking system that can continuously trace WiFi objects at decimeter-level in real-time. To enable this, we make three main proposals. The first one is a super-resolution localization scheme that combines compressed sensing and expectation-maximization algorithms to iteratively resolve multi-path, which realizes better resolution compared against traditional MUSIC. The second one is a customized particle filter that takes advantage of WiFi signals and the geometric nature of AOA estimates to properly update location states and particle weights. Finally, an SVD-based multipacket fusion is employed to reinforce the signal space and improve tracking efficiency at the same time. A prototype is built using only commercial WiFi NICs. Extensive experiments demonstrate that DeTrack achieves an 80th percentile localization accuracy of 0.9 meters and a median latency of around 90 milliseconds. As a result, DeTrack is looking to benefit a wide range of applications, e.g., indoor navigation, intelligent logistics, and smart cities.