THE FUTURE OF FLUXGATE MAGNETOMETERS: ENHANCING THREE-AXIS PRECISION WITH ADVANCED PARAMETER ESTIMATION

Abstract

With the wide application of fluxgate magnetometer sensor in the field of high-precision magnetic field measurement, the inconsistency between its three axes due to production process problems has attracted more and more attention. The purpose of this paper is to correct the measurement errors of the three axes of the sensor respectively, so as to improve the measurement accuracy of the magnetometer. In this paper, the particle filtering algorithm is used as the core, based on the error model of the fluxgate magnetometer, in which the nine correction parameters are updated and iterated, and after the importance resampling process, the parameter estimates are obtained and substituted into the error correction model, and then the error correction of the three-axis fluxgate is realized. The proposed method is verified by simulation and experimental data. The results show that the proposed method can effectively correct the triaxial error and improve the working performance of the sensor. Particle filter algorithm is an algorithm based on the spatial model of dynamic system, which has good filtering effect on nonlinear system. The research results of this paper are verified by examples, which is of great significance to improve and improve the measurement accuracy of fluxgate.