{"title":"RSSI localization algorithm based on RBF neural network","authors":"J. Tian, Zhan Xu","doi":"10.1109/ICSESS.2012.6269470","DOIUrl":null,"url":null,"abstract":"This paper proposes a algorithm method of RBF neural network based on RSSI localization algorithm. It solves the question which through traditional filter algorithm, redundancy algorithm can not solve base on effect of multi-route propagation, and the complexity of signal attenuation environment. Simulation results demonstrate the validity of the algorithm, it can mitigate the effect of multi-route propagation, and localization precision can reach one meter or higher. On the side, this algorithm have higher convergence speed, it fits in embedded application. It can be designed as self-study and closed loop neural network in future.","PeriodicalId":205738,"journal":{"name":"2012 IEEE International Conference on Computer Science and Automation Engineering","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE International Conference on Computer Science and Automation Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSESS.2012.6269470","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
This paper proposes a algorithm method of RBF neural network based on RSSI localization algorithm. It solves the question which through traditional filter algorithm, redundancy algorithm can not solve base on effect of multi-route propagation, and the complexity of signal attenuation environment. Simulation results demonstrate the validity of the algorithm, it can mitigate the effect of multi-route propagation, and localization precision can reach one meter or higher. On the side, this algorithm have higher convergence speed, it fits in embedded application. It can be designed as self-study and closed loop neural network in future.