RFID Indoor Positioning Algorithm Based on Antenna Coverage Model
摘要
Current positioning algorithms based on Radio Frequency Identification(RFID) location systems with dense passive tags face the issue of low localization precision due to the variation of behavior of tags,the ignorance of antenna directivity,external environment noise interference.To solve these problems and improve the positioning accuracy,the paper proposes a 2D passive RFID indoor positioning algorithm(IPABACM) by taking the directionality of the antenna into account in dense passive RFID tag distribution applications.Considering the effects of noise and tag performance differences in the production,the readied tags are assigned weights and trained through neural network.The deviation caused by antenna pattern’s uncertainty is eliminated by superimposing the antenna coverage area as a more regular pattern,which significantly improves the positioning accuracy.Experimental results show that compared with the traditional passive RFID localization algorithm,the IPABACM algorithm can provide relatively better accuracy and less positioning time.