Detection of vehicle tracks by a three-axis magnetometer

Zhang, Q.; Xiao, Li; Pan, Hailin; Wang, J.T.

doi:10.1016/j.sna.2018.03.016

Cited by 15 publications

(4 citation statements)

References 16 publications

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“…To validate the MAD model, a nonlinear non-diagonal threeaxis giant GMI sensor was used (Zhang et al, 2018). The threeaxis magnetic sensor we used is packaged in an aluminum housing consisted of a sensing element and a signal processing integrated circuit, as shown in Figure 8.…”

Section: Establish Systemmentioning

confidence: 99%

Design and optimization of sensor array for magnetic gradient tensor system

Chen

Zhu

Zhang

et al. 2020

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Purpose The differential magnetic gradient tensor system is usually constructed from the three-axis magnetic sensor array. While the effects of measurement error, sensor performance and baseline distance on localization performance of such systems have been widely reported, the research about the effect of spatial design of sensor array is less presented. This paper aims to provide a spatial design method of sensor array and corresponding optimization strategy to localization based on magnetic tensor gradient to get the optimum design of the sensor array. Based on the results of simulation, magnetic localization systems constructed from the proposed array and the traditional array have been built to carry out a localization experiment. The results of experiment have verified the effectiveness of magnetic localization based on the proposed array. Design/methodology/approach The authors focus on the localization of the magnetic target based on magnetic gradient by using three-axis magnetic sensor array and combine a design method with corresponding optimization strategy to get the optimum design of the sensor array. Findings This paper provides an array design and optimization method for magnetic target localization based on magnetic gradient to improve the localization performance. Originality/value In this paper, the authors focus on the magnetic localization based on magnetic gradient by using three-axis magnetic sensors and study the effect of the spatial design of sensor array on localization performance.

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Section: Establish Systemmentioning

confidence: 99%

Design and optimization of sensor array for magnetic gradient tensor system

Chen

Zhu

Zhang

et al. 2020

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“…Demoz Gebre Egziabher used the TWO-STEP algorithm and least square estimation to correct the experimental data of a three-axis magnetometer, and the results showed that the residual after correction was very small [ 15 ]. Zhang Dewen and others put forward a two-step correction method for the component error of a three-axis magnetic sensor to correct the total magnetic field and the components of the three-axis magnetic sensor [ 16 ]. Wang Lihui and others combined the total least square method with the regularization method to propose a truncated total least square method to deal with the ill-conditioned problem of random errors on both sides of the observation equation [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

A Compensation Method for the Geomagnetic Measurement Error of an Underwater Ship-Borne Magnetometer Based on Constrained Total Least Squares

Tong,

Huang,

Chen

et al. 2024

Sensors

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When magnetic matching aided navigation is applied to an underwater vehicle, the magnetometer must be installed inside the vehicle, considering the navigation safety and concealment of the underwater vehicle. Then, the interference magnetic field will seriously affect the accuracy of geomagnetic field measurement, which directly affects the accuracy of geomagnetic matching aided navigation. Therefore, improving the accuracy of geomagnetic measurements inside the vehicle through error compensation has become one of the most difficult problems that requires an urgent solution in geomagnetic matching aided navigation. In order to solve this problem, this paper establishes the calculation model of the internal magnetic field of the underwater vehicle and the geomagnetic measurement error model of the ship-borne magnetometer. Then, a compensation method for the geomagnetic measurement error of the ship-borne magnetometer, based on the constrained total least square method, is proposed. To verify the effectiveness of the method proposed in this paper, a simulation experiment of geomagnetic measurement and compensation of a ship-borne three-axis magnetometer was constructed. Among them, to be closer to the real situation, a combination of the geomagnetism model, the elliptic shell model and the magnetic dipole model was used to simulate the internal magnetic field of the underwater vehicle. The experimental results indicated that the root mean square error of geomagnetic measurement in an underwater vehicle was less than 5 nT after compensation, and the accuracy of geomagnetic measurement met the requirements of geomagnetic matching aided navigation.

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“…Magnetic anomaly detection (MAD) is an effective method for the detection and tracking of ferromagnetic targets, and for unexploded ordnance (UXO) detection, geophysical detection, and prospecting [1][2][3]. An array of magnetometers is often used to measure the magnetic gradient tensor, suppress interference from environmental background magnetic fields and improve the accuracy of the measurement [4,5].…”

Section: Introductionmentioning

confidence: 99%

“…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. This method requires high-precision calibration of the optical system and the initial coordinate system of the optical prism [17].…”

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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Detection of vehicle tracks by a three-axis magnetometer

Cited by 15 publications

References 16 publications

Design and optimization of sensor array for magnetic gradient tensor system

Design and optimization of sensor array for magnetic gradient tensor system

A Compensation Method for the Geomagnetic Measurement Error of an Underwater Ship-Borne Magnetometer Based on Constrained Total Least Squares

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

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