Calibration of three-axis magnetometers with alternative iteration looping optimization method

Abstract

PurposeThis study aims to find a novel solution to the calibration of three-axis magnetometers to suppress errors of sensors. The nature of the calibration process is parameter estimation and hence the purpose of the paper is to calculate the error parameters and eliminate sensor errors and obtain the true value of the pure magnetic field.Design/methodology/approachThe paper puts forward a calibration method using an alternative iteration looping optimization (AILO) to estimate the parameters. The proposed method divided the parameters to be estimated into two parts: a portion less than one and the other greater than one. Parameters with different orders of magnitude are calculated respectively, which let one part to be a known quantity and the other part is derived by the known quantity; the derived quantity is used to calculate the known quantity again, and looping iteration multiple times until the iteration termination condition is satisfied.FindingsThe simulation and experimental results indicate that the calibration accuracy is improved at least by two orders by the proposed method compared to the two-step method and the linear decreasing weight particle swarm optimization (LDW-PSO) algorithm which proves the validity of the proposed method.Practical implicationsThe proposed method can improve the calibration accuracy of total magnetic field, which provides a reference to the calibration of three-axis magnetometers.Originality/valueA calibration method based on the AILO is proposed in this paper, which is used to improve the calibration accuracy of the three-axis magnetometer.