Joint Calibration of Inertial Sensors and Magnetometers using von Mises-Fisher Filtering and Expectation Maximization
(2019) 22th International Conference on Information Fusion (FUSION)- Abstract
- Microelectromechanical-systems-based inertial sensors and magnetometers are low-cost, off-the-shelf sensors that are widely used in both consumer and industrial applications. However, these sensors suffer from biases and effects such as axis misalignment or scale errors, which require careful system design and periodic sensor calibration. In this paper, we propose a fast calibration method for jointly calibrating inertial sensors and magnetometers based on discrete-time von Mises-Fisher filtering and expectation maximization. We evaluate the method on built-in smartphone sensors and show that the proposed method efficiently estimates the sensors' parameters and reduces the overall error.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/e3930de7-8e53-4852-91cf-ddd1afa24254
- author
- Hostettler, Roland ; Garcia-Fernandez, Angel F ; Tronarp, Filip LU and Särkkä, Simo
- publishing date
- 2019
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- 2019 22th International Conference on Information Fusion (FUSION)
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 22th International Conference on Information Fusion (FUSION)
- conference location
- Ottawa, Canada
- conference dates
- 2019-07-02 - 2019-07-05
- DOI
- 10.23919/FUSION43075.2019.9011257
- language
- English
- LU publication?
- no
- id
- e3930de7-8e53-4852-91cf-ddd1afa24254
- date added to LUP
- 2023-08-21 02:14:58
- date last changed
- 2023-11-10 13:51:12
@inproceedings{e3930de7-8e53-4852-91cf-ddd1afa24254, abstract = {{Microelectromechanical-systems-based inertial sensors and magnetometers are low-cost, off-the-shelf sensors that are widely used in both consumer and industrial applications. However, these sensors suffer from biases and effects such as axis misalignment or scale errors, which require careful system design and periodic sensor calibration. In this paper, we propose a fast calibration method for jointly calibrating inertial sensors and magnetometers based on discrete-time von Mises-Fisher filtering and expectation maximization. We evaluate the method on built-in smartphone sensors and show that the proposed method efficiently estimates the sensors' parameters and reduces the overall error.}}, author = {{Hostettler, Roland and Garcia-Fernandez, Angel F and Tronarp, Filip and Särkkä, Simo}}, booktitle = {{2019 22th International Conference on Information Fusion (FUSION)}}, language = {{eng}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, title = {{Joint Calibration of Inertial Sensors and Magnetometers using von Mises-Fisher Filtering and Expectation Maximization}}, url = {{http://dx.doi.org/10.23919/FUSION43075.2019.9011257}}, doi = {{10.23919/FUSION43075.2019.9011257}}, year = {{2019}}, }