Indoor Localization Fusion Algorithm Based on Signal Filtering optimization Of Multi-sensor

Abstract

The environment for indoor positioning becomes increasingly complicated, making it difficult for accurate and fast positioning. To tackle the above problem, an indoor fusion positioning scheme is presented in this paper, in which Bluetooth, WiFi and RFID data are fused. KILA algorithm and improved Kalman filter algorithm are used to provide multiple fusion positioning schemes. The experiment results show that compared with the single positioning method and the traditional filtering algorithms, the proposed fusion method improves indoor positioning significantly and yields to less positioning errors.