A High-Precision Indoor Positioning Algorithm via Integration of Pedestrian Dead Reckoning and Visible Light Positioning on Mobile Devices

Pedestrian Dead Reckoning (PDR) locates pedestrians simply through the data collected by motion sensors without any external information assistance, making it ideal for indoor positioning scenarios. However, consumer-grade MEMS Inertial Measurement Units (IMUs) embedded in smartphones only provide low-quality data, resulting in poor positioning accuracy. In addition, their position errors also accumulated over time. In this paper, we investigate the integration of PDR with visible light positioning (VLP) to provide a continuous, reliable, high-precision indoor location estimation in mobile phones. The Extended Kalman filter (EKF) is used to fuse PDR and VLP, and then the relevant experimental scenario is set up to evaluate the algorithm's performance. The experimental results demonstrate that the proposed scheme can significantly enhance positioning accuracy, achieving an improvement of 26%~28% compared to PDR-only positioning.