The component compensation of geomagnetic field vector measurement system

Pang, Hongfeng; Zhu, Xiangwei; Pan, Mengchun; Zhang, Qi; Chen, Wan; Luo, Siqiang; Chen, Jinfei; Li, Ji; Lv, Yunxiao; Chen, Dixiang

doi:10.1016/j.jmmm.2015.01.031

Cited by 21 publications

(17 citation statements)

References 23 publications

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“…Currently, many studies are being conducted on overcoming hard-iron distortion and soft-iron distortion, which are external distortion factors [ 25 , 26 ]. However, these methods revise the characteristics of the magnetic field through post-processing; therefore, it is difficult to use them for positioning, which requires real-time processing.…”

Section: Related Theoriesmentioning

confidence: 99%

Real-Time Recursive Fingerprint Radio Map Creation Algorithm Combining Wi-Fi and Geomagnetism

Seong

Seo

2018

Sensors

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Fingerprint is a typical indoor-positioning algorithm, which measures the strength of wireless signals and creates a radio map. Using this radio map, the position is estimated through comparisons with the received signal strength measured in real-time. The radio map has a direct effect on the positioning performance; therefore, it should be designed accurately and managed efficiently, according to the type of wireless signal, amount of space, and wireless-signal density. This paper proposes a real-time recursive radio map creation algorithm that combines Wi-Fi and geomagnetism. The proposed method automatically recreates the radio map using geomagnetic radio-map dual processing (GRDP), which reduces the time required to create it. It also reduces the size of the radio map by actively optimizing its dimensions using an entropy-based minimum description length principle (MDLP) method. Experimental results in an actual building show that the proposed system exhibits similar map creation time as a system using a Wi-Fi–based radio map. Geomagnetic radio maps exhibiting over 80% positioning accuracy were created, and the dimensions of the radio map that combined the two signals were found to be reduced by 23.81%, compared to the initially prepared radio map. The dimensions vary according to the wireless signal state, and are automatically reduced in different environments.

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Section: Related Theoriesmentioning

confidence: 99%

Real-Time Recursive Fingerprint Radio Map Creation Algorithm Combining Wi-Fi and Geomagnetism

Seong

Seo

2018

Sensors

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“…As is known, the rotation matrix (attitude information) can be obtained by inertial sensors in time, which can be expressed as

C_{i}^{j} = ([], \begin{matrix} c_{11} & c_{12} & c_{13} \\ c_{21} & c_{22} & c_{23} \\ c_{31} & c_{32} & c_{33} \end{matrix})

with

({, \begin{matrix} c_{11} = \cos θ \cos φ \\ c_{12} = - \cos ϕ \sin φ + \sin ϕ \sin θ \sin φ \\ c_{13} = \sin ϕ \sin φ + \cos ϕ \sin θ \cos φ \\ c_{21} = \cos θ \sin φ \\ c_{22} = \cos ϕ \cos φ + \sin ϕ \sin θ \sin φ \\ c_{23} = - \sin ϕ \cos φ + \cos ϕ \sin θ \sin φ \\ c_{31} = - \sin θ \\ c_{32} = \sin ϕ \cos θ \\ c_{33} = \cos ϕ \cos θ \end{matrix})

where ϕ, θ, φ are the changes of yaw angle, roll angle, and pitch angle from the i th orientation to j th orientation in two different orientations.…”

Section: Compensation Theorymentioning

confidence: 99%

“…By minimizing the square of the differences between the norms of magnetometer outputs and the magnitude of the geomagnetic field, the error parameters of compensation model can be estimated using various algorithms. As a result, these traditional methods can compensate a scalar error but not a vector error . However, for geomagnetic vector measurement, the vector error must be reduced to the minimum to ensure measurement accuracy.…”

Section: Introductionmentioning

confidence: 99%

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Magnetic disturbance field compensation of a geomagnetic vector measuring instrument

Liu

Zhang

Pan

et al. 2017

IEEJ Transactions Elec Engng

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Magnetic disturbance field from ferromagnetic structural parts is a dominant factor that influences the accuracy of a geomagnetic vector measuring instrument. In this paper, a new vector compensation method for a three-axis magnetometer is proposed. In the first step, combined with posture information from inertial sensors, the dataset of the three-axis magnetometer outputs in different postures is utilized to construct linear equations of the error parameters; then the soft-iron parameters are determined with singular value decomposition. In the second step, the hard-iron parameters are estimated by changing the fixing direction of the three-axis magnetometer. Simulations and experiments are performed to assess the performance of the proposed method. The results show that the error parameters can be accurately estimated, and the measurement errors of geomagnetic field vectors and magnitude are suppressed greatly. After compensation, the standard deviations of the errors of the magnetic vector components decrease from hundreds of nT to tens of nT. The main advantages of this proposed method are as follows: (i) it can compensate not only the scalar error but also the vector error, and (ii) it compensates the errors of vectors and magnitude with higher accuracy.

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“…Little work has been done for magnetic distortion field component compensation. Pang et al [30] introduced a component compensation method, where a parallelepiped frame and perpendicular platform with designed operation process should be used. The key factor is to provide true magnetic components for three-axis magnetometer.…”

Section: Introductionmentioning

confidence: 99%

Improved component compensation for geomagnetic field vector measurement using Lagrange multiplier method

Chen

Pan

Zhang

et al. 2017

IET Science, Measurement & Technology

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The component compensation of geomagnetic field vector measurement system

Cited by 21 publications

References 23 publications

Real-Time Recursive Fingerprint Radio Map Creation Algorithm Combining Wi-Fi and Geomagnetism

Real-Time Recursive Fingerprint Radio Map Creation Algorithm Combining Wi-Fi and Geomagnetism

Magnetic disturbance field compensation of a geomagnetic vector measuring instrument

Improved component compensation for geomagnetic field vector measurement using Lagrange multiplier method

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