A Hybrid Dynamic-Kinematic EKF for Train Trajectory Estimation

This paper proposes a Hybrid Dynamic-Kinematic Extended Kalman Filter (EKF) for the online estimation of train position, velocity and acceleration along the track. In the proposed EKF commonly used kinematic measurements are fused with dynamic information, i.e. active power used, to obtain more accurate estimates. This also results in an onboard-only measurements based model that will enable the implementation of next generation traffic management systems. Two case studies, based on real data of train runs on a Swiss line, are presented to demonstrate the goodness of the proposed approach.