Error Calibration of Cross Magnetic Gradient Tensor System with Total Least-Squares Method

Cheng Chi, Dan Wang, Ronghua Tao, Zhentao Yu and Hamid M. Sedighi

Mathematical Problems in Engineering, 2022, vol. 2022, 1-13

Abstract: The magnetic gradient tensor system configured by fluxgate magnetometers is subjected to different scale factors, three-axis nonorthogonality, bias, and misalignment errors. All those errors above will influence the measurement precision directly, so the magnetic gradient tensor system must be calibrated before use. In this paper, an error calibration method of the magnetic gradient tensor system is proposed. The procedure of the proposed method is as follows. Firstly, the error calibration model of the single fluxgate magnetometer is established and generated an ellipsoid mathematical expression. To simplify the calculation, the ellipsoid mathematical expression is transformed into a linear model of intermediate variables, and then, error parameters are estimated by the total least-squares method. Secondly, the orthogonal procrustes problem is adopted to calibrate misalignment errors. Finally, simulations and experiments with a cross magnetic gradient tensor system are carried out for verification of the proposed error calibration method. Results show that compared with the original least-squares method, the proposed method can increase the measurement accuracy of the cross magnetic gradient tensor system greatly.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:6974834

DOI: 10.1155/2022/6974834

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