基于联合估计迭代算法的三轴磁力仪标定补偿方法

Calibration of Three-axis Fluxgate Magnetometers with Joint Estimation Iterative Algorithm

地磁场测量过程中,三轴磁力仪受到多种干扰因素的影响而产生误差,对测量精度造成影响。在分析地磁场测量值误差来源的基础上,建立了三轴磁力仪测量一体化模型,提出采用联合估计迭代算法对其进行标定,并比较了该方法与扩展卡尔曼滤波算法、非线性最小二乘算法的性能。在仿真结果基础上,构建实验系统对所提方法进行实验验证。仿真和实验结果表明:3种方法中,联合估计迭代算法补偿误差均值和标准差最小,且收敛速度最快,可将三轴磁力仪测量值误差均值由142.4 nT降至12.5 nT,标准差由170.0 nT降至29.2 nT,抑制比达到84.51%;为三轴磁力仪的标定补偿提供了一种有效的方法。

In the process of geomagnetic field measurement,the three-axis magnetometer is affected by various interference factors and produces various errors which have effect on the measurement accuracy.Based on the analysis of the error sources of measured values of geomagnetic field,an integrated model of three-axis magnetometer measurement is established.An joint estimation iterative algorithm is proposed to calibrate three-axis magnetometer.The performances of the proposed algorithm,extended Kalman filter(EKF)algorithm and nonlinear least squares algorithm are compared.Based on the simulated results,an experimental system was build to verify the proposed method.The simulated and experimental results show that,among the three algorithms,the joint estimation iterative algorithm compensates the error mean and standard deviation to the smallest,and its convergence speed is the fastest.The average error of measured values of three-axis magnetometer can be reduced from 142.4 nT to 12.5 nT,the standard deviation can be decreased from 170.0 nT to 29.2 nT,and the suppression ratio is 84.51%,which provides an effective method for the calibration compensation of three-axis magnetometer.