Magnetometer calibration is a pre-processing step in the Attitude and Heading Reference Systems (AHRS) which has an essential role in many applications. The main purpose of this article is to derive an innovative and precise calibration approach for a magnetometer set installed on human body. To execute this calibration method, all the error parameters of multiple magnetometers are considered in an Unscented Kalman Filter (UKF) model for accurate estimation of calibration parameters. As achieving a precise estimation in Kalman filters-based algorithms needs an accurate and complete observation model, a special single-axis rotation trajectory for Inertial Measurement Unit (IMU) is performed to increase the observability rank of the calibration model. To evaluate the proposed method, five body-mounted sensors were experimented in the laboratory at the same time for applying in the body motion capture system. The results showed that all five sensors were well-calibrated without any need to be detached from the body and using any rotational robot arm. The resolution and precision of the proposed calibration method are assessed by the ellipsoid-fitting representation method. Consequently, all the body-mounted magnetometers were calibrated, on average, by about 1% uncertainty. The method can be used in every motion capture and AHRS applications due to its feasibility and simplicity.
Published in | International Journal of Sensors and Sensor Networks (Volume 9, Issue 1) |
DOI | 10.11648/j.ijssn.20210901.11 |
Page(s) | 1-10 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2021. Published by Science Publishing Group |
Magnetometer Calibration, Calibration, Motion Capture, Magnetometer, Inertial Sensors, Unscented Kalman Filter, MEMS
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APA Style
Farzan Farhangian, Saoussen Bilel, Faramarz Farhangian, Rene Jr. Landry. (2021). A Magnetometer Calibration Method Using Single-Axis Motion Trajectory and Unscented Kalman Filter for Body Motion Capture Applications. International Journal of Sensors and Sensor Networks, 9(1), 1-10. https://doi.org/10.11648/j.ijssn.20210901.11
ACS Style
Farzan Farhangian; Saoussen Bilel; Faramarz Farhangian; Rene Jr. Landry. A Magnetometer Calibration Method Using Single-Axis Motion Trajectory and Unscented Kalman Filter for Body Motion Capture Applications. Int. J. Sens. Sens. Netw. 2021, 9(1), 1-10. doi: 10.11648/j.ijssn.20210901.11
AMA Style
Farzan Farhangian, Saoussen Bilel, Faramarz Farhangian, Rene Jr. Landry. A Magnetometer Calibration Method Using Single-Axis Motion Trajectory and Unscented Kalman Filter for Body Motion Capture Applications. Int J Sens Sens Netw. 2021;9(1):1-10. doi: 10.11648/j.ijssn.20210901.11
@article{10.11648/j.ijssn.20210901.11, author = {Farzan Farhangian and Saoussen Bilel and Faramarz Farhangian and Rene Jr. Landry}, title = {A Magnetometer Calibration Method Using Single-Axis Motion Trajectory and Unscented Kalman Filter for Body Motion Capture Applications}, journal = {International Journal of Sensors and Sensor Networks}, volume = {9}, number = {1}, pages = {1-10}, doi = {10.11648/j.ijssn.20210901.11}, url = {https://doi.org/10.11648/j.ijssn.20210901.11}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijssn.20210901.11}, abstract = {Magnetometer calibration is a pre-processing step in the Attitude and Heading Reference Systems (AHRS) which has an essential role in many applications. The main purpose of this article is to derive an innovative and precise calibration approach for a magnetometer set installed on human body. To execute this calibration method, all the error parameters of multiple magnetometers are considered in an Unscented Kalman Filter (UKF) model for accurate estimation of calibration parameters. As achieving a precise estimation in Kalman filters-based algorithms needs an accurate and complete observation model, a special single-axis rotation trajectory for Inertial Measurement Unit (IMU) is performed to increase the observability rank of the calibration model. To evaluate the proposed method, five body-mounted sensors were experimented in the laboratory at the same time for applying in the body motion capture system. The results showed that all five sensors were well-calibrated without any need to be detached from the body and using any rotational robot arm. The resolution and precision of the proposed calibration method are assessed by the ellipsoid-fitting representation method. Consequently, all the body-mounted magnetometers were calibrated, on average, by about 1% uncertainty. The method can be used in every motion capture and AHRS applications due to its feasibility and simplicity.}, year = {2021} }
TY - JOUR T1 - A Magnetometer Calibration Method Using Single-Axis Motion Trajectory and Unscented Kalman Filter for Body Motion Capture Applications AU - Farzan Farhangian AU - Saoussen Bilel AU - Faramarz Farhangian AU - Rene Jr. Landry Y1 - 2021/01/12 PY - 2021 N1 - https://doi.org/10.11648/j.ijssn.20210901.11 DO - 10.11648/j.ijssn.20210901.11 T2 - International Journal of Sensors and Sensor Networks JF - International Journal of Sensors and Sensor Networks JO - International Journal of Sensors and Sensor Networks SP - 1 EP - 10 PB - Science Publishing Group SN - 2329-1788 UR - https://doi.org/10.11648/j.ijssn.20210901.11 AB - Magnetometer calibration is a pre-processing step in the Attitude and Heading Reference Systems (AHRS) which has an essential role in many applications. The main purpose of this article is to derive an innovative and precise calibration approach for a magnetometer set installed on human body. To execute this calibration method, all the error parameters of multiple magnetometers are considered in an Unscented Kalman Filter (UKF) model for accurate estimation of calibration parameters. As achieving a precise estimation in Kalman filters-based algorithms needs an accurate and complete observation model, a special single-axis rotation trajectory for Inertial Measurement Unit (IMU) is performed to increase the observability rank of the calibration model. To evaluate the proposed method, five body-mounted sensors were experimented in the laboratory at the same time for applying in the body motion capture system. The results showed that all five sensors were well-calibrated without any need to be detached from the body and using any rotational robot arm. The resolution and precision of the proposed calibration method are assessed by the ellipsoid-fitting representation method. Consequently, all the body-mounted magnetometers were calibrated, on average, by about 1% uncertainty. The method can be used in every motion capture and AHRS applications due to its feasibility and simplicity. VL - 9 IS - 1 ER -