Real-Time UWB and IMU Fusion Positioning System for Urban Rail Transit with High Mobility

Urban rail transit is currently moving toward automated driving and mobile occlusion, which raises higher expectations for the train positioning system. Operating in diverse environments like open spaces and tunnels, a single positioning system falls short in meeting the accuracy and consistency requirements for train positioning along the entire rail line. In response to these stringent requirements, this research proposes an Error-State Kalman Filter (ESKF) based real-time fusion train positioning system for urban rail transit, incorporating Ultra-Wideband (UWB) and Inertial Measurement Unit (IMU) technologies. Through practical measurements, an UWB ranging error model is established. Based on this model, a simulation study is conducted on the proposed real-time fusion positioning algorithm under different UWB anchor deployment methods in the context of urban rail transit scenarios. The real-time performance and accuracy of the proposed algorithm were validated through in-tunnel testing.