{"title":"基于指纹和可见光通信的室内定位方法","authors":"Chuhan Zhao, Hongming Zhang, Jian Song","doi":"10.1109/ICAIT.2017.8388915","DOIUrl":null,"url":null,"abstract":"In this article, a fingerprint and visible light communication based indoor positioning method is proposed. This method recovers the optical wireless channel features and estimates the location of mobile terminal by these features. In order to reduce the computation complexity of the fingerprint-based positioning method, the proposed method combines triangulation and the nearest neighbor fingerprint algorithm. Firstly, triangulation is used to determine the cluster of probable locations of mobile terminal. The most probable location of mobile terminal within the cluster is then estimated by the nearest neighbor fingerprint algorithm. The simulation results show that the proposed method reduces fingerprint computation and achieves high accuracy in indoor localization.","PeriodicalId":376884,"journal":{"name":"2017 9th International Conference on Advanced Infocomm Technology (ICAIT)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Fingerprint and visible light communication based indoor positioning method\",\"authors\":\"Chuhan Zhao, Hongming Zhang, Jian Song\",\"doi\":\"10.1109/ICAIT.2017.8388915\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this article, a fingerprint and visible light communication based indoor positioning method is proposed. This method recovers the optical wireless channel features and estimates the location of mobile terminal by these features. In order to reduce the computation complexity of the fingerprint-based positioning method, the proposed method combines triangulation and the nearest neighbor fingerprint algorithm. Firstly, triangulation is used to determine the cluster of probable locations of mobile terminal. The most probable location of mobile terminal within the cluster is then estimated by the nearest neighbor fingerprint algorithm. The simulation results show that the proposed method reduces fingerprint computation and achieves high accuracy in indoor localization.\",\"PeriodicalId\":376884,\"journal\":{\"name\":\"2017 9th International Conference on Advanced Infocomm Technology (ICAIT)\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 9th International Conference on Advanced Infocomm Technology (ICAIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAIT.2017.8388915\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 9th International Conference on Advanced Infocomm Technology (ICAIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAIT.2017.8388915","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fingerprint and visible light communication based indoor positioning method
In this article, a fingerprint and visible light communication based indoor positioning method is proposed. This method recovers the optical wireless channel features and estimates the location of mobile terminal by these features. In order to reduce the computation complexity of the fingerprint-based positioning method, the proposed method combines triangulation and the nearest neighbor fingerprint algorithm. Firstly, triangulation is used to determine the cluster of probable locations of mobile terminal. The most probable location of mobile terminal within the cluster is then estimated by the nearest neighbor fingerprint algorithm. The simulation results show that the proposed method reduces fingerprint computation and achieves high accuracy in indoor localization.