Research on RFID indoor location algorithm based on WPA-BP

The conventional RSSI-based RFID positioning algorithm is extensively employed for indoor positioning. To enhance the accuracy of position coordinates and minimize errors, this paper proposes an innovative RSSI-based RFID indoor positioning algorithm that integrates the Wolf pack algorithm (WPA) and BP neural network. A WPA-BP hybrid neural network algorithm is the integration of WPA to optimize the weight and threshold of the BP neural network. Training samples for the BP neural network are derived from RSSI signal strength and tag coordinates measured by the RFID reader, while the WPA algorithm optimizes the threshold and weight values of the neural network, resulting in a WPA-BP neural network model algorithm. Compared with experimental results of indoor localization based on BP algorithm and WPA-BP algorithm, the results using WPA-BP hybrid algorithm reduces errors in RFID indoor positioning, mitigates the impact of environmental factors, and enhances overall performance based on RSSI. Kenwords : indoor positioning ; neural network ; wolf pack algorithm; Radio Frequency Identification