Train Localization During GNSS Outages: A Minimalist Approach Using Track Geometry And IMU Sensor Data
arxiv(2024)
Abstract
Train localization during Global Navigation Satellite Systems (GNSS) outages
presents challenges for ensuring failsafe and accurate positioning in railway
networks. This paper proposes a minimalist approach exploiting track geometry
and Inertial Measurement Unit (IMU) sensor data. By integrating a discrete
track map as a Look-Up Table (LUT) into a Particle Filter (PF) based solution,
accurate train positioning is achieved with only an IMU sensor and track map
data. The approach is tested on an open railway positioning data set, showing
that accurate positioning (absolute errors below 10 m) can be maintained during
GNSS outages up to 30 s in the given data. We simulate outages on different
track segments and show that accurate positioning is reached during track
curves and curvy railway lines. The approach can be used as a redundant
complement to established positioning solutions to increase the position
estimate's reliability and robustness.
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