The component compensation of geomagnetic field vector measurement system

Purpose The geomagnetic field vector is a function of the satellite’s position. The position and speed of the satellite can be determined by comparing the geomagnetic field vector measured by on board three-axis magnetometer with the standard value of the international geomagnetic field. The geomagnetic model has the disadvantages of uncertainty, low precision and long-term variability. Therefore, accuracy of autonomous navigation using the magnetometer is low. The purpose of this paper is to use the geomagnetic and sunlight information fusion algorithm to improve the orbit accuracy. Design/methodology/approach In this paper, an autonomous navigation method for low earth orbit satellite is studied by fusing geomagnetic and solar energy information. The algorithm selects the cosine value of the angle between the solar light vector and the geomagnetic vector, and the geomagnetic field intensity as observation. The Adaptive Unscented Kalman Filter (AUKF) filter is used to estimate the speed and position of the satellite, and the simulation research is carried out. This paper also made the same study using the UKF filter for comparison with the AUKF filter. Findings The algorithm of adding the sun direction vector information improves the positioning accuracy compared with the simple geomagnetic navigation, and the convergence and stability of the filter are better. The navigation error does not accumulate with time and has engineering application value. It also can be seen that AUKF filtering accuracy is better than UKF filtering accuracy. Research limitations/implications Geomagnetic navigation is greatly affected by the accuracy of magnetometer. This paper does not consider the spacecraft’s environmental interference with magnetic sensors. Practical implications Magnetometers and solar sensors are common sensors for micro-satellites. Near-Earth satellite orbit has abundant geomagnetic field resources. Therefore, the algorithm will have higher engineering significance in the practical application of low orbit micro-satellites orbit determination. Originality/value This paper introduces a satellite autonomous navigation algorithm. The AUKF geomagnetic filter algorithm using sunlight information can obviously improve the navigation accuracy and meet the basic requirements of low orbit small satellite orbit determination.

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Multifrequency Vector Measurement System for Reliable Vehicle Magnetic Profile Assessment

Sensors ◽

10.3390/s20174933 ◽

2020 ◽

Vol 20 (17) ◽

pp. 4933 ◽

Cited By ~ 1

Author(s):

Zbigniew Marszalek ◽

Krzysztof Duda

Keyword(s):

Measurement System ◽

Impedance Measurement ◽

Operational Mode ◽

Front End ◽

Vector Measurement ◽

Field Programmable ◽

Excitation Frequencies ◽

Magnetic Profile ◽

Analogue To Digital ◽

Parameters Measurement

This paper describes the design and the performance of simultaneous, multifrequency impedance measurement system for four inductive-loop (IL) sensors which have been developed for vehicle parameters measurement based on vehicle magnetic profile (VMP) analysis. Simultaneous impedance measurement on several excitation frequencies increases the VMP measurement reliability because typical electromagnetic interferences (EMI) are narrowband, and should not simultaneously affect, in the same way, all measurement bands that are spread in the frequency, i.e., it is expected that at least one measurement band is disturbance-free. The system consists of two standard and two slim IL sensors, specially designed and installed, the analogue front-end, and an industrial computer with digital-to-analogue and analogue-to-digital converters accessed via field-programmable gate array (FPGA). The impedance of the IL sensors is obtained by vector measurement of voltages from auto-balancing bridge (ABB) front-end. Complex voltages are demodulated from excitation frequencies with FIR filters designed with the flat-top windows. The system is capable of delivering VMPs in real-time mode, and also storing voltages for off-line postprocessing and analysis. Field distributions and sensitivities of slim and standard IL sensors are also discussed. Field test confirmed assumed increased reliability of VMP measurement for proposed simultaneous multifrequency operational mode.

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Correlation based snapshot models of the archeomagnetic field

Geophysical Journal International ◽

10.1093/gji/ggaa336 ◽

2020 ◽

Vol 223 (1) ◽

pp. 648-665

Author(s):

S Mauerberger ◽

M Schanner ◽

M Korte ◽

M Holschneider

Keyword(s):

Model Uncertainty ◽

Geomagnetic Field ◽

A Priori ◽

Field Vector ◽

Parametric Approach ◽

Full Field ◽

The Past ◽

Uncertainty Estimates ◽

Improved Model ◽

Field Estimate

SUMMARY For the time stationary global geomagnetic field, a new modelling concept is presented. A Bayesian non-parametric approach provides realistic location dependent uncertainty estimates. Modelling related variabilities are dealt with systematically by making little subjective a priori assumptions. Rather than parametrizing the model by Gauss coefficients, a functional analytic approach is applied. The geomagnetic potential is assumed a Gaussian process to describe a distribution over functions. A priori correlations are given by an explicit kernel function with non-informative dipole contribution. A refined modelling strategy is proposed that accommodates non-linearities of archeomagnetic observables: First, a rough field estimate is obtained considering only sites that provide full field vector records. Subsequently, this estimate supports the linearization that incorporates the remaining incomplete records. The comparison of results for the archeomagnetic field over the past 1000 yr is in general agreement with previous models while improved model uncertainty estimates are provided.

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Magnetometer Measurement System for the Parameters of the Geomagnetic Field

Measurement Techniques ◽

10.1007/s11018-016-1003-4 ◽

2016 ◽

Vol 59 (5) ◽

pp. 532-536 ◽

Cited By ~ 4

Author(s):

A. I. Zaiko ◽

A. V. Vorob’ev ◽

G. A. Ivanova ◽

G. R. Shakirova

Keyword(s):

Measurement System ◽

Geomagnetic Field

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