李青竹, 李志宁, 张英堂, 范红波, 尹刚. 磁梯度张量系统的非线性集成矢量校正[J]. 武汉大学学报 ( 信息科学版), 2019, 44(5): 714-722, 730. DOI: 10.13203/j.whugis20170161
引用本文: 李青竹, 李志宁, 张英堂, 范红波, 尹刚. 磁梯度张量系统的非线性集成矢量校正[J]. 武汉大学学报 ( 信息科学版), 2019, 44(5): 714-722, 730. DOI: 10.13203/j.whugis20170161
LI Qingzhu, LI Zhining, ZHANG Yingtang, FAN Hongbo, YIN Gang. Integrated Vector Calibration of Magnetic Gradient Tensor System Using Nonlinear Method[J]. Geomatics and Information Science of Wuhan University, 2019, 44(5): 714-722, 730. DOI: 10.13203/j.whugis20170161
Citation: LI Qingzhu, LI Zhining, ZHANG Yingtang, FAN Hongbo, YIN Gang. Integrated Vector Calibration of Magnetic Gradient Tensor System Using Nonlinear Method[J]. Geomatics and Information Science of Wuhan University, 2019, 44(5): 714-722, 730. DOI: 10.13203/j.whugis20170161

磁梯度张量系统的非线性集成矢量校正

Integrated Vector Calibration of Magnetic Gradient Tensor System Using Nonlinear Method

  • 摘要: 磁梯度张量系统测量精度受到单磁传感器系统误差与传感器阵列间非对准误差的严重影响。为了获得精确的张量测量输出,建立了单磁传感器零漂、标度因子与非正交角等系统误差和多传感器轴系间非对准误差的集成数学模型,提出了基于十字磁梯度张量系统最小二乘非线性集成校正方法。相比两步标量校正,利用建立的集成数学模型能够一次性估计出十字形张量系统的48个误差参数,以"人造"平台输出为参考实现低成本矢量校正,极大提高了校正效率和参数估计准确率。仿真和实测表明,张量系统误差参数仿真估计准确率高于99.75%,实验校正后总场输出均方根误差(root mean square error,RMSE)小于2 nT,张量分量RMSE小于50 nT/m,参数估计具有较高的鲁棒性。

     

    Abstract: In order to obtain the accurate output of the tensor measurement, an integrated mathematical model of sensor biases, scale factors and non-orthogonality error of single magnetic sensor and the misalignment error between multi-sensor axes is established. Based on the cross magnetic gradient tensor system, a least-squares nonlinear integrated calibration method is proposed. Compared with the twostep scalar calibration, the integrated mathematical model can be used to estimate the entire 48 error parameters of the cross tensor system at once, and a low-cost vector calibration is realized using an man-made platform out-put as the reference, which greatly improves the calibration efficiency and accuracy of parameters estimated. Simulation and experiment results show that the accuracy of the error parameters' estimation of the tensor system is higher than 99.75%, the root mean square error of the total field intensity output is less than 2 nT and the root mean square error of the tensor component is less than 50 nT/m.

     

/

返回文章
返回