Calibration of three-axis magnetometers with differential evolution algorithm

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• 作者：Hongfeng Pang ; Qi Zhang ; Wei Wang ; Junya Wang ; Ji Li ; Shitu Luo ; Chengbiao Wan ; Dixiang Chen ; Mengchun Pan ; Feilu Luo
• 关键词：Three-axis magnetometer ; Nonmagnetic rotation platform ; Differential evolution (DE) ; Unscented Kalman filter (UKF) ; Genetic algorithm (GA) ; Recursive least squares (RLS)
• 刊名：Journal of Magnetism and Magnetic Materials
• 出版年：2013
• 出版时间：November, 2013
• 年：2013
• 卷：346
• 期：Complete
• 页码：5-10
• 全文大小：1191 K

文摘

The accuracy of three-axis magnetometers is influenced by different scale and bias of each axis and nonorthogonality between axes. One limitation of traditional iteration methods is that initial parameters influence the calibration, thus leading to the local optimal or wrong results. In this paper, a new method is proposed to calibrate three-axis magnetometers. To employ this method, a nonmagnetic rotation platform, a proton magnetometer, a DM-050 three-axis magnetometer and the differential evolution (DE) algorithm are used. The performance of this calibration method is analyzed with simulation and experiment. In simulation, the calibration results of DE, unscented Kalman filter (UKF), recursive least squares (RLS) and genetic algorithm (GA) are compared. RMS error using DE is least, which is reduced from 81.233 nT to 1.567 nT. Experimental results show that comparing with UKF, RLS and GA, the DE algorithm has not only the least calibration error but also the best robustness. After calibration, RMS error is reduced from 68.914 nT to 2.919 nT. In addition, the DE algorithm is not sensitive to initial parameters, which is an important advantage compared with traditional iteration algorithms. The proposed algorithm can avoid the troublesome procedure to select suitable initial parameters, thus it can improve the calibration performance of three-axis magnetometers.