Snapshot Estimator for Magnetic Field-based Train Localization with Uncalibrated Magnetometers

Kurzfassung

Magnetic field-based train localization uses distortions of the Earth magnetic field caused by magnetic material in the vicinity of the tracks. From the distortions, a position estimate can be obtained by comparing magnetometer measurements to a map of the magnetic field. The comparison to the map requires the calibration of the train-mounted magnetometer. However, calibration is difficult because common calibration techniques require a rotation of the magnetometer and the platform it is mounted on. Thus, in this paper we propose a maximum likelihood (ML) snapshot estimator that simultaneously estimates the calibration parameters and the train position. The snapshot estimator reduces the ML estimation problem to a onedimensional optimization problem that can be solved efficiently. To show the feasibility of the approach, an evaluation is carried out based on measurements recorded with a train driving through Berlin.