RBF neural network based RFID indoor localization method using artificial immune system

Indoor location based service is more and more popular in our daily lives. Due to such advantages of low power consumption, large interrogation range and low deployment cost, the Radio Frequency IDentification (RFID) becomes a simple, cost-effective indoor localization technology in indoor location based service systems. However, some existing RFID indoor localization methods are yet not satisfactory in accuracy. This paper proposes an Artificial Immune System based Radial Basis Function Neural Network (AIS-RBF-NN) to realize RFID indoor localization, in which artificial immune system is used to optimize the center vector selection of radial basis functions. To counteract the effect of the scene noise, the differences between the Received Signal Strength Indication (RSSI) values are fed into AIS-RBF- NN as well as RSSI values themselves. Simulation results indicate that the proposed AIS-RBF-NN based RFID indoor localization method is effective and outperforms the existing method.