Intelligent Fusion Structure for Wi-Fi/BLE/QR/MEMS Sensor-Based Indoor Localization

Due to the complexity of urban environments, localizing pedestrians indoors using mobile terminals is an urgent task in many emerging areas. Multi-source fusion-based localization considered be effective way provide location-based services large-scale indoor This paper presents intelligent 3D framework that uses integration Wi-Fi, Bluetooth Low Energy (BLE), quick response (QR) code, and micro-electro-mechanical system sensors (the 3D-WBQM framework). An enhanced inertial odometry was developed for accurate pedestrian trajectory optimization spaces containing magnetic interference external acceleration, Wi-Fi fine time Measurement stations, BLE nodes, QR codes were applied landmark detection absolute reference crowdsourced navigation database construction. In addition, robust unscented Kalman filter (RUKF) as a generic integrated model combine estimated location results from odometry, BLE, QR, FTM, fingerprinting positioning. The experimental indicated proposed verified realize autonomous positioning performance areas different sources, meter-level accuracy can acquired FTM supported