Magnetic interference compensation method for geomagnetic field vector measurement

Measurement ◽  
2016 ◽  
Vol 91 ◽  
pp. 628-633 ◽  
Author(s):  
Qi Zhang ◽  
Hongfeng Pang ◽  
Chengbiao Wan
2017 ◽  
Vol 11 (8) ◽  
pp. 1094-1098 ◽  
Author(s):  
Chengbiao Wan ◽  
Mengchun Pan ◽  
Qi Zhang ◽  
Hongfeng Pang ◽  
Xuejun Zhu ◽  
...  

Measurement ◽  
2020 ◽  
Vol 164 ◽  
pp. 108041
Author(s):  
Hongfeng Pang ◽  
Mengchun Pan ◽  
Wei Qu ◽  
Lei Qiu ◽  
Jun Yang ◽  
...  

2015 ◽  
Vol 381 ◽  
pp. 390-395 ◽  
Author(s):  
Hongfeng Pang ◽  
Xue Jun Zhu ◽  
Mengchun Pan ◽  
Qi Zhang ◽  
Chengbiao Wan ◽  
...  

2013 ◽  
Vol 373-375 ◽  
pp. 811-814
Author(s):  
Jun Wei Lv ◽  
Zhen Tao Yu ◽  
Li Heng Fan

It is unavoidable that the geomagnetic field measurement is interfered by the vehicle magnetic field in geomagnetic navigation. In order to improve the measurement accuracy, the magnetic interference of vehicle must be correctly compensated. Based on the ellipse fitting compensation method, a new 3D magnetic interference compensation method is proposed. The proposed method improves the vehicle magnetic interference compensation method from 2D ellipse fitting to 3D ellipsoid fitting by the least square algorithm of ellipsoid restriction, which relaxes the restriction on 2D motion of vehicles. And a computing method of the compensation parameters is proposed to decrease the load of calculation. Finally, the experiment shows that the compensation method can compensate the vehicle 3D magnetic interference efficiently.


2018 ◽  
Vol 11 (4) ◽  
pp. 471-485 ◽  
Author(s):  
Bing Hua ◽  
Zhiwen Zhang ◽  
Yunhua Wu ◽  
Zhiming Chen

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.


2020 ◽  
Vol 223 (1) ◽  
pp. 648-665
Author(s):  
S Mauerberger ◽  
M Schanner ◽  
M Korte ◽  
M Holschneider

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.


IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 152728-152737
Author(s):  
Hongfeng Pang ◽  
Wei Qu ◽  
Yuntao Li ◽  
Jun Yang ◽  
Mengchun Pan ◽  
...  

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