Mapping the magnetic field using a magnetometer array with noisy input
Gaussian process regression
- URL: http://arxiv.org/abs/2310.16577v1
- Date: Wed, 25 Oct 2023 12:00:45 GMT
- Title: Mapping the magnetic field using a magnetometer array with noisy input
Gaussian process regression
- Authors: Thomas Edridge and Manon Kok
- Abstract summary: A Gaussian process can be used to learn the spatially varying magnitude of the magnetic field.
The position of the magnetometer, however, is frequently only approximately known.
In this paper, we investigate how an array of magnetometers can be used to improve the quality of the magnetic field map.
- Score: 1.0878040851637998
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Ferromagnetic materials in indoor environments give rise to disturbances in
the ambient magnetic field. Maps of these magnetic disturbances can be used for
indoor localisation. A Gaussian process can be used to learn the spatially
varying magnitude of the magnetic field using magnetometer measurements and
information about the position of the magnetometer. The position of the
magnetometer, however, is frequently only approximately known. This negatively
affects the quality of the magnetic field map. In this paper, we investigate
how an array of magnetometers can be used to improve the quality of the
magnetic field map. The position of the array is approximately known, but the
relative locations of the magnetometers on the array are known. We include this
information in a novel method to make a map of the ambient magnetic field. We
study the properties of our method in simulation and show that our method
improves the map quality. We also demonstrate the efficacy of our method with
experimental data for the mapping of the magnetic field using an array of 30
magnetometers.
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