Hybrid Calibration Method for Three-Axis Gradiometer

Yang, Zhicheng; Yan, Shefeng; Li, Bin

doi:10.1109/lmag.2017.2740838

Cited by 7 publications

(6 citation statements)

References 25 publications

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“…where A is the integrated error parameter including sensitivity errors, nonorthogonality errors, and soft-iron effect errors [25], b is the integrated error including offset errors and hard-iron effect errors, B s m is the magnetic field generated by the magnet, B s e is the disturbing magnetic field including geomagnetic field and surrounding disturbance, and n B is the measurement noise. A and b can be estimated by calibration procedures [26], [27].…”

Section: A Magnetic Source and Sensor Modelmentioning

confidence: 99%

Estimate Hand–Finger Position With One Magnetometer and Known Relative Orientation

Yang

Yan

Beijnum

et al. 2021

IEEE Trans. Instrum. Meas.

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Inertial-sensor-based hand motion tracking has become a well-accepted method in many clinical applications, including rehabilitation of the upper extremity. However, major drawbacks are that a sensor on each segment and kinematic chain rule is required. Thus, errors accumulate through the kinematic chain rule. Also, the length of each segment needs to be measured for each user. We propose a novel method in which a permanent magnet on the dorsal side of the hand combined with an inertial and magnetic measurement unit (IMMU) on the fingertip is used to estimate the position of the thumb and index fingertip relative to the position of the dorsal side of the hand. The biggest advantages of the proposed method are that no prior information and kinematic chain rule are needed. Besides, the required number of sensors is low. A Levenberg-Marquardt (L-M) approach is presented to estimate the relative positions with the known orientations. The performance is demonstrated in multiple experiments in which various movement tasks were performed. The most complex task in which participants performed reaching and grasping movements based on the action research arm test (ARAT) resulted in a median distance error between thumb and index finger of 9.6%.

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Section: A Magnetic Source and Sensor Modelmentioning

confidence: 99%

Estimate Hand–Finger Position With One Magnetometer and Known Relative Orientation

Yang

Yan

Beijnum

et al. 2021

IEEE Trans. Instrum. Meas.

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“…(1) The magnetometers are first mounted on a non-magnetic rigid support, which is rotated in a relatively uniform magnetic field in accordance with certain rules. Then, using the principle of a constant magnetic gradient tensor, each error parameter of the magnetometer array, including the bias, non-orthogonal error and mismatch error, are calculated with the least-squares method or other algorithm, and the measurement results are calibrated [7][8][9][10][11][12][13][14][15][16]. (2) The optical calibration method, which uses regular hexahedral optical prisms and orthogonal optical systems as references for measuring and correcting mismatch errors.…”

Section: Introductionmentioning

confidence: 99%

Calibration method for mismatch error of a magnetometer array based on two excitation coils and the particle swarm optimization algorithm

Wang

Liu

Ouyang

et al. 2020

Meas. Sci. Technol.

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In performing the detection and tracking of ferromagnetic targets or the detection of magnetic anomalies, a magnetometer array or magnetic gradiometer is often used to suppress interference from environmental background magnetic fields and to improve measurement accuracy. Increasing the distance between the magnetometers is beneficial to improving the signal-to-noise ratio (SNR) of the magnetic gradiometer, but the mismatching error of the magnetometer array affects the accuracy in measuring the magnetic gradient tensor and the positioning accuracy of the ferromagnetic target. In order to calibrate the mismatch error of a magnetometer array, the mounting position and orientation of each magnetometer must be accurately measured. When the magnetometer array is too large, the commonly used calibration methods are difficult to implement because it is difficult to make a rigid support, optical system or robot that is large enough. This paper reports a method that uses two coils and an excitation current source to generate a test magnetic field, after which methods of modulation/demodulation and phase-locked filtering are used to suppress interference from the ambient magnetic field. The output of each magnetometer is recorded, and the particle swarm optimization algorithm is employed to calculate the mounting position and orientation of each magnetometer. After theoretical analysis, computational simulation and experimental verification, the results showed that position measurements over an area of 2.4 m × 2.4 m were accurate to within 0.05 m and the orientation measurements were accurate to within 0.03 rad. The average relative positioning error was less than 1.7%. By designing larger coils and current sources, the needs of larger arrays can be satisfied as long as the same SNR is maintained.

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“…Yang et al introduced a hybrid calibration method for triaxis gradiometers. This method is suitable for the calibration of systems with two or more TAMs [15].…”

Section: Introductionmentioning

confidence: 99%

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

Yang¹,

Li²,

Chen³

2018

Meas. Sci. Technol.

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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.

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Hybrid Calibration Method for Three-Axis Gradiometer

Cited by 7 publications

References 25 publications

Estimate Hand–Finger Position With One Magnetometer and Known Relative Orientation

Estimate Hand–Finger Position With One Magnetometer and Known Relative Orientation

Calibration method for mismatch error of a magnetometer array based on two excitation coils and the particle swarm optimization algorithm

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

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