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Magnetic field distortion of INS is the major factor influencing the accuracy of geomagnetic field information measurement system. Simulation and experiment results show that traditional scalar compensation methods are disabled for component compensation. A component compensation method is proposed, in which parallelepiped frame and perpendicular platform are used with designed operation process. Comparing with traditional methods, the component compensation method is effective for distortion parameter estimation, and it shows better component compensation performance. Experimental test result demonstrates that distortion field components of INS are suppressed approximately two orders after compensation, and the North, Vertical and East component measurement error of the geomagnetic field are reduced to 2.3%, 3.3% and 4.5% of the former values respectively. Declination error is reduced from 7.074° to 0.331° (4.6% of the former value). This compensation method contributes to the accuracy improvement of geomagnetic field vector measurement system.

Magnetic distortions such as eddy-current field and low frequency magnetic field have not been considered in vector compensation methods. A new compensation method is proposed to suppress these magnetic distortions and improve compensation performance, in which the magnetic distortions related to measurement vectors and time are considered. The experimental system mainly consists of a three-axis fluxgate magnetometer (DM-050), an underwater vehicle and a proton magnetometer, in which the scalar value of magnetic field is obtained with the proton magnetometer and considered to be the true value. Comparing with traditional compensation methods, experimental results show that the magnetic distortions can be further reduced by two times. After compensation, error intensity and RMS error are reduced from 11684.013 nT and 7794.604 nT to 16.219 nT and 5.907 nT respectively. It suggests an effective way to improve the compensation performance of magnetic distortions.

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.