Calibration of strapdown magnetic vector measurement systems based on a plane compression method

被引:4
|
作者
Li, Supeng [1 ]
Cheng, Defu [1 ,2 ]
Wang, Yi [1 ]
Zhao, Jing [1 ,2 ]
机构
[1] Jilin Univ, Coll Instrumentat & Elect Engn, Changchun, Peoples R China
[2] Jilin Univ, Key Lab Geophys Explorat Equipment, Changchun, Peoples R China
基金
中国国家自然科学基金;
关键词
magnetic vector measurement system; magnetometer error; misalignment error; inertial navigation system; MAGNETOMETER; INVERSION;
D O I
10.1088/1361-6501/acbab0
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The strapdown magnetic vector measurement system, which can measure the magnetic vector and the attitude of a magnetometer simultaneously, has wide applications in geophysical prospecting, etc. Calibration of systematic errors, including magnetometer errors and misalignment errors, is essential for this system. Traditional methods calibrate these two errors separately, with the problem of cumbersome steps and being dependent on special data acquisition methods, such as rotation. An original method that combines a plane compression method with an ellipsoid fitting method is proposed in this paper, which can simultaneously complete the calibration calculation of magnetometer error and misalignment error in one experiment. The calculation can be performed using the spatial scatter point data required by the traditional attitude-independent magnetometer calibration method, and no additional mechanical equipment is required. A mathematical analysis of this method is performed to study the elements decreasing the measurement accuracy of the system, and numerical simulation and field experiments are performed to validate the analysis. The results indicate that the method can contribute to the accuracy improvement of magnetic vector measurement systems.
引用
收藏
页数:9
相关论文
共 50 条
  • [1] A novel vector magnetic measurement system calibration method based on geomagnetic variation
    Liu, Ji-hao
    Li, Xi-hai
    Niu, Chao
    Zeng, Xiao-niu
    Zhang, Yun
    APPLIED GEOPHYSICS, 2025, 22 (01) : 35 - 42
  • [2] Artificial Vector Calibration Method for Differencing Magnetic Gradient Tensor Systems
    Li, Qingzhu
    Li, Zhining
    Zhang, Yingtang
    Yin, Gang
    SENSORS, 2018, 18 (02):
  • [3] Error Analysis Technique for Indirect Method of Calibration of a Strapdown Inertial Measurement Unit
    Vodicheva, L.
    Parysheva, Yu.
    2019 26TH SAINT PETERSBURG INTERNATIONAL CONFERENCE ON INTEGRATED NAVIGATION SYSTEMS (ICINS), 2019,
  • [4] Velocity measurement method based on the principle of magnetic flux compression
    Chi Xiaoping
    Lv Qingao
    Xiang Hongjun
    Zhi Bin'an
    Guan Xiaocun
    ISTM/2007: 7TH INTERNATIONAL SYMPOSIUM ON TEST AND MEASUREMENT, VOLS 1-7, CONFERENCE PROCEEDINGS, 2007, : 921 - 924
  • [5] Test bed calibration of fog-based strapdown inertial measurement unit
    G. I. Emel’yantsev
    E. V. Dranitsyna
    B. A. Blazhnov
    Gyroscopy and Navigation, 2012, 3 (4) : 265 - 269
  • [6] A method for polarization scattering parameter measurement and calibration based on vector network analyzer
    Kang, H.-B. (khb2000@163.com), 2013, Beijing University of Posts and Telecommunications (20):
  • [7] Three-Degree-of-Freedom Measurement Method Based on Plane Normal Vector
    Fang Guoming
    Peng Qi
    Ma Haotong
    Qiao Shan
    Bian Jiang
    Chen Feng
    Liu Xincheng
    Tan Yufeng
    He Bi
    Dong Li
    LASER & OPTOELECTRONICS PROGRESS, 2018, 55 (11)
  • [8] A Novel Plane-Based Probe Tip Calibration Method for Stereo Measurement and Navigation
    Liu, Mingbo
    Sun, Tieyuan
    Han, Ye
    Liu, Jianshuang
    You, Xiaolong
    Liu, Lubin
    TEHNICKI VJESNIK-TECHNICAL GAZETTE, 2025, 32 (02): : 517 - 525
  • [9] Enhanced Vector Calibration of Load-pull Measurement Systems
    Aldoumani, A.
    Williams, Tudor
    Lees, J.
    Tasker, P. J.
    2014 83RD ARFTG MICROWAVE MEASUREMENT CONFERENCE (ARFTG): MICROWAVE MEASUREMENTS FOR EMERGING TECHNOLOGIES, 2014,
  • [10] An Autocollimator Axial Measurement Method Based on the Strapdown Inertial Navigation System
    Ma, Wenjia
    Li, Jianrong
    Liu, Shaojin
    Han, Yan
    Liu, Xu
    Wang, Zhiqian
    Jiang, Changhong
    SENSORS, 2024, 24 (08)