Calibration of tri-axis magnetometers using an improved truncated singular value decomposition method

Abstract

The performance of a three-axis magnetometer (TAM) is limited by various types of error; hence, the system must be calibrated prior to use. The convergence of calibration algorithms is quite sensitive to input data, and divergence yields incorrect parameter-estimation results when the maneuvers of TAM are constrained. Therefore, a calibration method, based primarily on improved truncated singular value decomposition, was proposed. The singular values were divided into groups; the small values were modified, whereas the large values were retained (without modification). Information with improved accuracy was obtained from these large values, while the less accurate information contained in the smaller values was modified, thereby avoiding divergent solutions. The experimental results revealed that the performance of TAM was significantly improved by the use of the proposed calibration method.

A Designed Calibration Approach for the Measurement-While-Drilling Instrument

“…The above descriptions indicate that these errors must be eliminated appropriately for the gaining of the attitude information from the MWD instrument. The counterparts have acknowledged that the error elimination is contingent upon the deployment of the calibration algorithms [13][14][15][16][17][18][19][20][21][22][23]. However, they ignored the method of obtaining the sampled data.…”

“…Long et al [18] proposed a fast calibration method specific for a spinning projectile based on the ellipsoid fitting method. Yang et al [19] improved the ellipsoid fitting method with a truncated singular value decomposition method to enhance the success rate of calibration. It is notable that the above-mentioned studies have an underlying assumption: that is, the axes of the sensor triplet are aligned with the axes of the carrier platform.…”