{"title":"基于RSSI的距离测量无线定位校正算法","authors":"Ji Xiong, Qin Qin, Kemin Zeng","doi":"10.1109/ISCID.2014.246","DOIUrl":null,"url":null,"abstract":"In order to improve the localization precision based on Received Signal Strength Indicator (RSSI) distance measurement for wireless sensor network nodes, a correction RSSI localization algorithm is proposed. In the algorithm, the optimal beacon nodes are firstly taken into consideration, and then using the median mean filtering method to process the measured RSSI data from the optimal beacon nodes. Finally, the weighted centroid algorithm is used to obtain the unknown node location. The simulation results indicate that compared with the traditional RSSI algorithm, the localization error of correction algorithm is reduced by more than 60%, effectively improving the localization precision.","PeriodicalId":385391,"journal":{"name":"2014 Seventh International Symposium on Computational Intelligence and Design","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"A Distance Measurement Wireless Localization Correction Algorithm Based on RSSI\",\"authors\":\"Ji Xiong, Qin Qin, Kemin Zeng\",\"doi\":\"10.1109/ISCID.2014.246\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to improve the localization precision based on Received Signal Strength Indicator (RSSI) distance measurement for wireless sensor network nodes, a correction RSSI localization algorithm is proposed. In the algorithm, the optimal beacon nodes are firstly taken into consideration, and then using the median mean filtering method to process the measured RSSI data from the optimal beacon nodes. Finally, the weighted centroid algorithm is used to obtain the unknown node location. The simulation results indicate that compared with the traditional RSSI algorithm, the localization error of correction algorithm is reduced by more than 60%, effectively improving the localization precision.\",\"PeriodicalId\":385391,\"journal\":{\"name\":\"2014 Seventh International Symposium on Computational Intelligence and Design\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 Seventh International Symposium on Computational Intelligence and Design\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISCID.2014.246\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Seventh International Symposium on Computational Intelligence and Design","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCID.2014.246","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Distance Measurement Wireless Localization Correction Algorithm Based on RSSI
In order to improve the localization precision based on Received Signal Strength Indicator (RSSI) distance measurement for wireless sensor network nodes, a correction RSSI localization algorithm is proposed. In the algorithm, the optimal beacon nodes are firstly taken into consideration, and then using the median mean filtering method to process the measured RSSI data from the optimal beacon nodes. Finally, the weighted centroid algorithm is used to obtain the unknown node location. The simulation results indicate that compared with the traditional RSSI algorithm, the localization error of correction algorithm is reduced by more than 60%, effectively improving the localization precision.