Six sigma constrained online calibration method for magnetometers

Jiaxin Liu; Yu Liu

doi:10.1117/12.3012558

21 December 2023 Six sigma constrained online calibration method for magnetometers

Jiaxin Liu, Yu Liu

Proceedings Volume 12970, Fourth International Conference on Signal Processing and Computer Science (SPCS 2023); 129701P (2023) https://doi.org/10.1117/12.3012558
Event: Fourth International Conference on Signal Processing and Computer Science (SPCS 2023), 2023, Guilin, China

Abstract

Online calibration of traditional magnetometers requires the assistance of inertial sensors, resulting in complex calculations and unstable accuracy. To this end, a six sigma constrained online calibration method for magnetometers is proposed, which reclassifies the errors of magnetometers and constructs an accurate magnetometer error model. Use Six Sigma (SS) to manage the calibration model of magnetometers and achieve error classification of magnetometers. A six sigma constrained extended Kalman filter (SEKF) method is proposed to calibrate the magnetometer error. The experimental results show that in the aspect of heading correction, the heading Root-mean-square deviation of the proposed magnetometer online calibration method is reduced by more than 32% and 12% respectively compared with the gyroscope assisted (GA) method and the extended Kalman filter calibration (EKF) method. A high-precision online self-calibration method for magnetometers without inertial sensor assistance has been implemented.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jiaxin Liu and Yu Liu "Six sigma constrained online calibration method for magnetometers", Proc. SPIE 12970, Fourth International Conference on Signal Processing and Computer Science (SPCS 2023), 129701P (21 December 2023); https://doi.org/10.1117/12.3012558

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