Analysis and Correction of the Magnetometer’s Position Error in a Cross-Shaped Magnetic Tensor Gradiometer

Abstract

When using the technique of magnetic gradient tensor measurements to obtain the position of magnetic objects, calibration of the magnetic tensor gradiometer plays a pivotal role in precisely locating the target, and extensive research has been carried out on this up to now. However, previous studies have always lacked sufficient discussion on the position error of magnetometers in magnetic tensor gradiometers caused by inaccurate installment of magnetometers. In this paper, we analyze and correct this position error based on a magnetic dipole source. The result of the simulation exemplifies that the magnetometer’s position error will affect the locating accuracy and, therefore, it is worth correcting this error. The relationship between position error and magnetic gradient tensor components is established, followed by an error correction method based on this relationship. Simulations illustrate that this method can effectively decrease the effect caused by the position error of magnetometers and improve the locating performance with locating error and magnetic moment errors dropping from 2 to 0.2 m and 6 × 10 5 A ⋅ m 2 to 5 × 10 4 A ⋅ m 2 , respectively.

Alignment error correction of five-sensor planar cross magnetic gradient tensor system

“…And the root mean square error is used to analyze the measured tensor data. The calculation formula of root mean square error is shown in Eq (8). Where, r  is the estimated value, ei  is the true value, and N is the number of measurement point.…”

“…Chen et al applied an array design and optimization method to the magnetic positioning algorithm based on magnetic gradient tensor, and studied the effect of sensor array space design on positioning in a multi-sensor magnetic gradient tensor system [7]. Yan et al analyzed and corrected the position error of the magnetometer in the cross-type magnetic tensor gradiometer [8].…”

Fast Localization of Underground Targets by Magnetic Gradient Tensor and Gaussian-Newton Algorithm With a Portable Transient Electromagnetic System

“…Accordingly, the DE algorithm is extremely time-consuming (several to tens of seconds) due to thousands of iterations. Magnetic gradient tensor can estimate target position with a single point and has been widely used in magnetic detection [31][32][33][34]. Generally, the localization accuracy is affected by the signal-to-noise ratio (SNR), sensor size, target depth, etc.…”

Research on the magnetic flux leakage field distribution characteristics of defect in low-frequency electromagnetic detection technique

“…Meanwhile, the highsensitivity magnetoresistive (MR) sensor is always adopted as the signal acquisition medium [19,20,21], although it is affected greatly by spatial magnetic field. In addition, the magnetic dipole model [22,23,24,25,26,27,28,29,30] is one of the most mature theories used to explain the magnetic flux leakage field produced by an external DC or a permanent magnet, which can also directly analyze the relative change trend of LF-MFL field instead of the absolute value variation. In this study, the mathematical models of the LF-MFL field spatial distribution for four types of groove crack defects (rectangular, semicircular, trapezoidal, and V-shaped) with equal lengths and widths were established on the basis of the derivation of magnetic dipole theory.…”