Localization With Magnetic Field Distortions and Simultaneous Magnetometer Calibration

Magnetic field localization utilizes position dependent and time persistent distortions of the earth magnetic field. These distortions are introduced by stationary ferromagnetic material in the environment and can be stored in a map to enable localization. Estimating the position of a magnetometer w...

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Bibliographic Details
Published in:IEEE sensors journal 2021-02, Vol.21 (3), p.3388-3397
Main Authors: Siebler, Benjamin, Sand, Stephan, Hanebeck, Uwe D.
Format: Article
Language:English
Subjects:
Calibration
Distortion
Ferromagnetic materials
Geomagnetic field
Industrial plants
Kalman filters
Localization
magnetic field localization
Magnetic fields
Magnetic sensors
Magnetic separation
Magnetometer calibration
Magnetometers
Maneuvers
Parameter estimation
Process parameters
Railroad cars
Rao-Blackwellized particle filtering
Time dependence
Transportation systems
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Summary:Magnetic field localization utilizes position dependent and time persistent distortions of the earth magnetic field. These distortions are introduced by stationary ferromagnetic material in the environment and can be stored in a map to enable localization. Estimating the position of a magnetometer with these distortions requires a calibration of the sensor to enable the matching of the measurements to the map. Typically, the calibration is performed in a prior step and requires specific maneuvers like sensor rotations in a homogenous field. The goal of the maneuvers is to render the calibration parameters observable. For heavy platforms, e.g., cars, trains and driverless transport systems in factories, performing special maneuvers is cumbersome or even impossible. In addition they operate in an environment with an inhomogeneous magnetic field. To address this issue, this article proposes a novel method that exploits the magnetic field distortions to render the calibration parameters observable. To simplify the calibration process, the calibration parameters are estimated simultaneously with the position of the platform. The method employs a Rao-Blackwellized particle filter that reduces the computational complexity and enables real time processing. The feasibility of the method is shown in an evaluation with measurements of a magnetometer mounted on a model train. The results show a high accuracy of the position and calibration parameter estimation.
ISSN:1530-437X
1558-1748
DOI:10.1109/JSEN.2020.3024073