Measurement Characteristics of Different Integrated Three-Dimensional Magnetic Field Sensors

Beran, Philip S.; Klohn, Maximilian; Hohe, Hans-Peter

doi:10.1109/lmag.2019.2944581

Cited by 7 publications

(9 citation statements)

References 8 publications

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“…The third component, VX, is influenced by projection BX of the magnetic flux density vector. In contrast to the previously mentioned two voltage components, this one has the opposite signs on potential electrodes 6 and 7: VX(6) = -VX (7). Particularly, under the influence of the Lorentz force in the top part (Fig.…”

Section: Structure and Operation Principlementioning

confidence: 75%

“…In [7] measurement characteristics of different integrated 3D magnetic field sensors were studied, whereas [8] discussed planarization, fabrication, and characterization. Crosstalk analysis and current measurement correction in circular 3D magnetic sensors arrays were given in [9].…”

Section: Literature Overviewmentioning

confidence: 99%

“…The first component, VR, is caused by voltage drop at semiconductor active area 2. Taking into account that the active area is symmetric with respect to the first current electrode 3, the first components of the voltage on potential electrodes 6 and 7 are equal: VR(6) = VR (7). The second component, VZ, is caused by projection BZ of the magnetic flux density vector that is perpendicular to the transducer plane.…”

Section: Structure and Operation Principlementioning

confidence: 99%

“…The second component, VZ, is caused by projection BZ of the magnetic flux density vector that is perpendicular to the transducer plane. Taking into account the transducer design and current flow directions in it, the second components of the voltage on potential electrodes 6 and 7 are equal as well, i.e., VZ(6) = VZ (7). The third component, VX, is influenced by projection BX of the magnetic flux density vector.…”

Section: Structure and Operation Principlementioning

confidence: 99%

See 3 more Smart Citations

Structure and 3-D Model of a Solid State Thin-Film Magnetic Sensor

Barylo

Holyaka

Marusenkova

et al. 2021

Phys. Chem. Solid St.

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Vector 3-D magnetic sensors form the basis of measurement devices for magnetic field mapping and magnetic tracking. Typically, such sensors utilize specific constructions based on split Hall structures (SHS). An SHS-based 3-D magnetic sensor is a bulk semiconductor integrated structure with 8 or more contacts. Combining current flow directions through the contacts and measuring the corresponding voltages, one defines projections BX, BY, BZ of the magnetic field vector. This work presents a novel design of 3-D solid state magnetic sensors that requires no insulation by p-n junctions and can be implemented by thin-film technology traditionally used for fabrication of Hall sensors including those based on InSb films. Besides, a SPICE model of the 3-D magnetic sensor is provided, which helps design the proposed sensor and refine techniques of its calibration.

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Section: Structure and Operation Principlementioning

confidence: 75%

Section: Literature Overviewmentioning

confidence: 99%

Section: Structure and Operation Principlementioning

confidence: 99%

Section: Structure and Operation Principlementioning

confidence: 99%

See 2 more Smart Citations

Structure and 3-D Model of a Solid State Thin-Film Magnetic Sensor

Barylo

Holyaka

Marusenkova

et al. 2021

Phys. Chem. Solid St.

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show abstract

“…Magnetic sensors are based on the transduction of different physical phenomena, as for instance the Electromagnetic Induction, Hall Effect, Tunnel Magnetoresistance (TMR), Giant Magnetoresistance (GMR), Anisotropic Magnetoresistance (AMR) and Giant Magnetoimpedance (GMI), [18]. The knowledge of the three Cartesian components of the magnetic field at the same time with a single miniaturized transducer is a great challenge for the semiconductor industry, [19], [20], [21]. In literature, detection techniques such as AMR or GMI are preferred for high-frequency magnetic field, due to their larger bandwidth, and for low magnetic fields (less than 1 mT).…”

Section: Introductionmentioning

confidence: 99%

Numerical and Experimental Estimation of Measurement Uncertainty in Magnetic Field Mapping

Marca

Tarabini

Lerch

et al. 2022

IEEE Trans. Instrum. Meas.

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This paper proposes a general method to model and simulate the process of magnetic field mapping; aim of our work is the combination of the effect of the bench position uncertainty with the magnetic measurements' uncertainty. The method is based on the study of the positioner kinematics using a multi-body system approach. The geometrical errors of the manipulator, including the manufacturing tolerances and the assembling non-idealities are included in the model using the homogeneous transformation matrix, to numerically estimate the end effector positioning uncertainty Up. The positioning uncertainty is then combined with the magnetic measurement uncertainty using the magnetic field gradient as a sensitivity coefficient; in presence of strong field non-linearities, the combination can be performed using Monte Carlo simulations in order to estimate how Up propagates to the magnetic measurement uncertainty U f at different positions. The method has been validated in the specific case of the Compact Field Mapper, a bench featuring a Cartesian robot and a triaxial Hall sensor used to measure flux density maps in the accessible region of interest of the magnets of the Swiss Light Source, with an uncertainty below 0.5 %. The method allowed to define, during the design phase, the characteristics of the positioning system (i.e. the mechanical positioning uncertainty Up) in order to obtain the desired magnetic measurement uncertainty U f . Simulations and experiments in the case of a reference quadrupole are presented and discussed.

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Magnetometer Calibration and Missile Attitude Filtering Method Based on Energy Estimation

Yan

Dunzhuo²,

Zhao³

et al. 2022

IEEE Access

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Estimating the flying attitude of the missile body during flight is vitally important for the intelligent ammunition. The earlier and more accurate the posture information is obtained, the more conducive it is to the control process of the intelligent ammunition. The magnetometer is commonly used to measure the roll attitude of the missile. However, the cumbersome calibration steps and noise interference of the missile usually cause the delay in the attitude calculation and inaccurate measurement. To solve these issues, an adaptive reconfigurable unscented Kalman filter (ARUKF) method based on energy estimation is proposed. The magnetic field measured by the magnetometer is analyzed in real time based on the roll characteristic of the intelligent ammunition to achieve the initial calibration of the magnetometer parameters. With the obtained calibrated parameters, the filter state variables are estimated by establishing the residual estimation function in the UKF, which guides the reconstruction of the UKF to minimize the computational cost of the attitude estimation process. Simultaneously, the on-board computer system feeds back the action of the rudder system in real time to guide the configuration of the noise parameters in the UKF process, which can effectively reduce the interference of the magnetic field generated by the rudder system on the attitude estimation. The numerical simulation and experiments show that the proposed method performs better in terms of parameter convergence speed and estimation accuracy, compared with the traditional UKF method, which has great application prospect in the field of intelligent ammunition.

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Measurement Characteristics of Different Integrated Three-Dimensional Magnetic Field Sensors

Cited by 7 publications

References 8 publications

Structure and 3-D Model of a Solid State Thin-Film Magnetic Sensor

Structure and 3-D Model of a Solid State Thin-Film Magnetic Sensor

Numerical and Experimental Estimation of Measurement Uncertainty in Magnetic Field Mapping

Magnetometer Calibration and Missile Attitude Filtering Method Based on Energy Estimation

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