Research on RFID Indoor Localization Algorithm Based on Virtual Tags and Fusion of LANDMARC and Kalman Filter

With the increase in demand for indoor positioning accuracy, the traditional LANDMARC algorithm introduces numerous tags leading to interferences between them. To address this issue and reduce costs, a new RFID indoor positioning algorithm was proposed. This novel approach was based on the integration of the Kalman filter and LANDMARC algorithm, along with the introduction of virtual tags. The primary aim of this algorithm was to reduce deployment cost and positioning errors while achieving more precise tag motion and position change descriptions. Moreover, this algorithm utilized the signal strength model of LANDMARC and the estimation results of the Kalman filter to infer and correct the target position with nuance. Simulation experiments show that the algorithm produces reliable results with high positioning accuracy, robustness, and adaptability.