J. Carrera, Zan Li, Zhongliang Zhao, T. Braun, A. Neto
{"title":"智能手机的实时室内跟踪系统","authors":"J. Carrera, Zan Li, Zhongliang Zhao, T. Braun, A. Neto","doi":"10.1145/2988287.2989142","DOIUrl":null,"url":null,"abstract":"The rapid growth area of ubiquitous applications and location-based services has made indoor localization an interesting topic for research. Some indoor localization solutions for smartphones exploit radio information and Inertial Measurement Units (IMUs), which are embedded in most of the modern smartphones. In this work, we propose to fuse WiFi Receiving Signal Strength Indicator (RSSI) readings, IMUs, and floor plan information in an enhanced particle filter to achieve high accuracy and stable performance in the tracking process. We provide an efficient double resampling method to mitigate errors caused by off-the-shelf IMUs and WiFi sensors embedded in commodity smartphones. The algorithms are designed in a terminal-based system, which consists of commercial smartphones and WiFi access points. We evaluate our system in two complex environments along moving paths. Experiment results show that our tracking method can achieve the average tracking error of $1.01$ meters and $90\\%$ accuracy of $1.7$ meters.","PeriodicalId":158785,"journal":{"name":"Proceedings of the 19th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems","volume":"75 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"A Real-time Indoor Tracking System in Smartphones\",\"authors\":\"J. Carrera, Zan Li, Zhongliang Zhao, T. Braun, A. Neto\",\"doi\":\"10.1145/2988287.2989142\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The rapid growth area of ubiquitous applications and location-based services has made indoor localization an interesting topic for research. Some indoor localization solutions for smartphones exploit radio information and Inertial Measurement Units (IMUs), which are embedded in most of the modern smartphones. In this work, we propose to fuse WiFi Receiving Signal Strength Indicator (RSSI) readings, IMUs, and floor plan information in an enhanced particle filter to achieve high accuracy and stable performance in the tracking process. We provide an efficient double resampling method to mitigate errors caused by off-the-shelf IMUs and WiFi sensors embedded in commodity smartphones. The algorithms are designed in a terminal-based system, which consists of commercial smartphones and WiFi access points. We evaluate our system in two complex environments along moving paths. Experiment results show that our tracking method can achieve the average tracking error of $1.01$ meters and $90\\\\%$ accuracy of $1.7$ meters.\",\"PeriodicalId\":158785,\"journal\":{\"name\":\"Proceedings of the 19th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems\",\"volume\":\"75 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-11-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 19th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2988287.2989142\",\"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 19th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2988287.2989142","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The rapid growth area of ubiquitous applications and location-based services has made indoor localization an interesting topic for research. Some indoor localization solutions for smartphones exploit radio information and Inertial Measurement Units (IMUs), which are embedded in most of the modern smartphones. In this work, we propose to fuse WiFi Receiving Signal Strength Indicator (RSSI) readings, IMUs, and floor plan information in an enhanced particle filter to achieve high accuracy and stable performance in the tracking process. We provide an efficient double resampling method to mitigate errors caused by off-the-shelf IMUs and WiFi sensors embedded in commodity smartphones. The algorithms are designed in a terminal-based system, which consists of commercial smartphones and WiFi access points. We evaluate our system in two complex environments along moving paths. Experiment results show that our tracking method can achieve the average tracking error of $1.01$ meters and $90\%$ accuracy of $1.7$ meters.