HPPS: A Head-Mounted Pedestrian Positioning System Integrating Fisheye Camera/RTK/PDR With Factor Graph Optimization

Substations are critical infrastructures in modern power systems, requiring accurate and reliable personnel positioning to ensure operational safety and inspection efficiency. Pedestrian dead reckoning (PDR) technology has emerged as a preferred solution for real-time, seamless positioning due to its autonomous, antijamming and passive characteristics. However, in practical applications, the PDR algorithm faces challenges such as the inability to provide absolute positioning due to unknown starting points and cumulative errors over time. To address these challenges, this article proposes a head-mounted pedestrian positioning system (HPPS) integrating a fisheye camera/real-time kinematic (RTK)/PDR based on factor graph optimization (FGO). First, a skyward-facing fisheye camera identifies nonline-of-sight (NLOS) signals caused by architectural obstructions, improving the absolute positioning accuracy of RTK. Next, an adaptive pedestrian gait detection and step length estimation (SLE) algorithm based on head-mounted inertial measurement units (IMUs) is developed to enhance PDR robustness. Finally, the FGO framework integrates the inputs of the fisheye camera, RTK, and PDR to achieve seamless indoor–outdoor positioning. Experimental results demonstrate that the proposed system achieves horizontal root-mean-square error (RMSE) values of less than 0.42 and 0.35 m in two distinct outdoor substation environments and less than 1.36 m in indoor–outdoor scenarios. This work highlights the integration of precise positioning technologies within the Internet of Things (IoT) framework, advancing smart grid applications and enabling effective location tracking in complex environments.