Floor-Plan-Assisted Fusion Positioning Using Bluetooth and Pedestrian Dead Reckoning

Digital twins are closely related to accurate positioning technologies, while floor-plans are promising prior information that can be viewed as the virtual model of the indoor environment and help enhance indoor positioning accuracy. However, existing research typically faces challenges in efficiently leveraging map information and handling complex indoor layouts. To tackle this issue, we propose a floor-plan-assisted fusion positioning algorithm using Bluetooth low energy (BLE) and pedestrian dead reckoning (FP-BP). In the considered system, the user holding a smartphone passes through an indoor area with BLE beacons installed on the ceiling, and can locate himself in real-time. FP-BP’s offline phase programmatically extracts the precise boundaries of various map features in the floor-plan, and establishes the functional relationship between coordinates and their corresponding map features. In the online phase, FP-BP fuses the received BLE signals and PDR sensor data with a particle filter to obtain an initial estimation, and then performs post-position correction to obtain the final position based on its specific map feature. Experimental results show that FP-BP can achieve a mean positioning accuracy of 1.33 m, which is improved by 24% compared to the baseline without the assistance of the floor-plan.