{"title":"基于关系聚合的RFID室内定位","authors":"Jiali Zheng, Tuanfa Qin, Jieming Wu, Li Wan","doi":"10.1109/ICACI.2016.7449800","DOIUrl":null,"url":null,"abstract":"This paper proposes a relational aggregation algorithm based on Radio Frequency Identification (RFID) to achieve accurate indoor localization. The proposed algorithm is composed of three steps: (1) exploring the relationship between reader received power and distance information then estimating Euclid distance of signal strength; (2) employing k-Nearest Neighbour algorithm to aggregate the relationship between nearest reference tag and target tag; (3) optimizing relational aggregation operator to obtain the coordinate of target tag. Simulated experiments show that the proposed algorithm can reduce mean localization error effectively and improve the accuracy of indoor localization.","PeriodicalId":211040,"journal":{"name":"2016 Eighth International Conference on Advanced Computational Intelligence (ICACI)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"RFID indoor localization based on relational aggregation\",\"authors\":\"Jiali Zheng, Tuanfa Qin, Jieming Wu, Li Wan\",\"doi\":\"10.1109/ICACI.2016.7449800\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a relational aggregation algorithm based on Radio Frequency Identification (RFID) to achieve accurate indoor localization. The proposed algorithm is composed of three steps: (1) exploring the relationship between reader received power and distance information then estimating Euclid distance of signal strength; (2) employing k-Nearest Neighbour algorithm to aggregate the relationship between nearest reference tag and target tag; (3) optimizing relational aggregation operator to obtain the coordinate of target tag. Simulated experiments show that the proposed algorithm can reduce mean localization error effectively and improve the accuracy of indoor localization.\",\"PeriodicalId\":211040,\"journal\":{\"name\":\"2016 Eighth International Conference on Advanced Computational Intelligence (ICACI)\",\"volume\":\"56 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 Eighth International Conference on Advanced Computational Intelligence (ICACI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICACI.2016.7449800\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Eighth International Conference on Advanced Computational Intelligence (ICACI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICACI.2016.7449800","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
RFID indoor localization based on relational aggregation
This paper proposes a relational aggregation algorithm based on Radio Frequency Identification (RFID) to achieve accurate indoor localization. The proposed algorithm is composed of three steps: (1) exploring the relationship between reader received power and distance information then estimating Euclid distance of signal strength; (2) employing k-Nearest Neighbour algorithm to aggregate the relationship between nearest reference tag and target tag; (3) optimizing relational aggregation operator to obtain the coordinate of target tag. Simulated experiments show that the proposed algorithm can reduce mean localization error effectively and improve the accuracy of indoor localization.