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Magnetometer calibration improvement using wavelet and genetic algorithm
Author(s) -
Hu Xiangchao,
Pang Hongfeng,
Fu Liangrui,
Pan Mengchun
Publication year - 2016
Publication title -
ieej transactions on electrical and electronic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 30
eISSN - 1931-4981
pISSN - 1931-4973
DOI - 10.1002/tee.22345
Subject(s) - magnetometer , wavelet , calibration , algorithm , scalar (mathematics) , kalman filter , noise (video) , physics , computer science , mathematics , acoustics , artificial intelligence , magnetic field , statistics , geometry , quantum mechanics , image (mathematics)
Three‐axis magnetometer error and measurement noise influence the accuracy of magnetic measurements. Genetic algorithm (GA) is proposed to calibrate the magnetometer error, and wavelet is proposed for noise cancellation. The noise of a Mag3300 magnetometer and a DM magnetometer were tested within a horizontal barrel shield equipment. Five kinds of wavelet analysis and two kinds of wavelet package were used for noise cancellation, and the performance of different wavelets was compared. Noise of the Mag3300 magnetometer and DM magnetometer were suppressed from 29.6 and 2.3466 to 3.7 and 1.0789 nT, respectively. The scalar error of the Mag3300 magnetometer was tested using a two‐dimensional nonmagnetic rotation equipment and a GSM‐19T proton magnetometer. Scalar calibration performances of the unscented Kalman filter (UKF), the two‐step algorithm, and GA were compared. Experimental results show that GA provides less error intensity (about 370 and 70 nT) than UKF and the two‐step algorithm. In addition, the influence of wavelet on scalar calibration using UKF, the two‐step algorithm, and GA was analyzed. Results show that wavelet improved the scalar calibration performance. Mean error of the Mag3300 magnetometer scalar was 795.5 nT. When combined with the wavelet package, the error was suppressed to −22.3, 3.3, and −0.4 nT using UKF, the two‐step algorithm, and GA, respectively. The results suggest an effective way for magnetometer calibration using GA and wavelet. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.