Research on error compensation in the process of geomagnetic sensor measurement

Zhang, Pingan; Wang, Wei; Gao, Ming; Wang, Yi

doi:10.1177/15501477211019911

Cited by 2 publications

(2 citation statements)

References 22 publications

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“…The error calibration problem of geomagnetic sensors is essentially a nonlinear optimization problem. The standard solution is the least square (LS) [12][13][14] method. This method only considers the observation matrix error and assumes that the random noise has a Gaussian distribution.…”

Section: Introductionmentioning

confidence: 99%

Improved ellipsoid fitting aided geomagnetic sensor calibration algorithm

Jiang,

Tan

2024

Meas. Sci. Technol.

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Aiming at the problems that the traditional single ellipsoid fitting fails to eliminate the errors of the geomagnetic sensor and does not consider the geomagnetic anomaly information, etc., this paper proposes a Robust Least Squares combined with the Levenberg-Marquardt (LM-RLS) algorithm to fit an accurate ellipsoid to achieve accurate data calibration. According to the geomagnetic sensor error model, the total amount of geomagnetism is used as the constraint, the fitted ellipsoid coefficients of Robust Least Squares (RLS) are used as the initial values, and the LM algorithm is used to calculate the magnetic field dispersion points to the nearest point of the fitted ellipsoid surface. Then, the initial calibration value is solved by the criterion of the minimum weighted sum of squares of the closest point distance. Finally, the accurate ellipsoid is obtained to realize data calibration. The results of the dynamic experiment show that after the ellipsoid is precisely fitted by the LM-RLS algorithm, the sum of the absolute values of the distance from the magnetic field discrete data to the ellipsoid surface is reduced by 48.33% (RLS) and 43.10% (RWTLS). The relative errors of the magnetic field in the X, Y, and Z axes are reduced from 0.48%, 0.78%, 1.48% (RLS) and 0.30%, 0.58%, 1.14% (RWTLS) to 0.10%, 0.04%, 0.16 %, respectively. The accuracy of geomagnetic calibration is improved by 68.06% (RLS) and 61.02% (RWTLS) in the dynamic experiment. The algorithm improves the accuracy of geomagnetic measurement, which provides a new idea for the calibration of three-axis geomagnetic sensors.

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Section: Introductionmentioning

confidence: 99%

Improved ellipsoid fitting aided geomagnetic sensor calibration algorithm

Jiang,

Tan

2024

Meas. Sci. Technol.

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“…In order to improve the accuracy of attitude calculation, it is necessary to obtain more accurate data. Ellipse fitting based on the least squares method is often used to correct the magnetometer data to improve the measurement accuracy [2,3]. Zhang et al [4] effectively extracted the gravity acceleration signal using a correlation-based detection method, but how to accurately extract the z-axis gravity acceleration needs to be further studied.…”

Section: Introductionmentioning

confidence: 99%

Attitude Calculation Method of Drilling Tools Based on Cross-Correlation Extraction and ASRUKF

Qin,

Wang,

Shi

et al. 2024

Electronics

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As a key component of the measurement while drilling technology, the accuracy of attitude calculation is directly related to the efficiency of resource exploration. To reduce the influence of vibration, rotation, and other disturbances on the attitude sensor during drilling, a method based on cross-correlation extraction and the adaptive square-root unscented Kalman filter (ASRUKF) is proposed to solve the attitude of the drilling tool in this paper. Firstly, the error of the signal collected by the attitude sensor is compensated, and the unscented Kalman filter (UKF) is used for filtering. Then, the effective gravitational acceleration signal is extracted by the cross-correlation method. Finally, an experimental platform for simulating the fully rotating attitude measurement system is established, and the application effects of the UKF and ASRUKF in the attitude calculation are compared. Compared with the UKF, the root mean square error of the inclination angle calculated by the ASRUKF is reduced by 12.9%, and the variance is reduced by 27.3%; the root mean square error of the azimuth angle is reduced by 29.5%, and the variance is reduced by 39.9%. The experimental results show that the attitude calculation method proposed in this paper can stably and effectively improve the accuracy of the attitude calculation of drilling tools.

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Research on error compensation in the process of geomagnetic sensor measurement

Cited by 2 publications

References 22 publications

Improved ellipsoid fitting aided geomagnetic sensor calibration algorithm

Improved ellipsoid fitting aided geomagnetic sensor calibration algorithm

Attitude Calculation Method of Drilling Tools Based on Cross-Correlation Extraction and ASRUKF

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