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Magnetometer-based autonomous orbit determination via a measurement differencing extended Kalman filter during geomagnetic storms

Feng Cui (National Space Science Center, Chinese Academy of Sciences, Beijing, China; Key Laboratory of Electronics and Information Technology for Space Systems, Chinese Academy of Sciences, Beijing, China and University of Chinese Academy of Sciences, Beijing, China)
Dong Gao (National Space Science Center, Chinese Academy of Sciences, Beijing, China; Key Laboratory of Electronics and Information Technology for Space Systems, Chinese Academy of Sciences, Beijing, China and University of Chinese Academy of Sciences, Beijing, China)
Jianhua Zheng (National Space Science Center, Chinese Academy of Sciences, Beijing, China; Key Laboratory of Electronics and Information Technology for Space Systems, Chinese Academy of Sciences, Beijing, China and University of Chinese Academy of Sciences, Beijing, China)

Aircraft Engineering and Aerospace Technology

ISSN: 0002-2667

Article publication date: 19 February 2020

Issue publication date: 19 March 2020

134

Abstract

Purpose

The main reason for the low accuracy of magnetometer-based autonomous orbit determination is the coarse accuracy of the geomagnetic field model. Furthermore, the geomagnetic field model error increases obviously during geomagnetic storms, which can still further reduce the navigation accuracy. The purpose of this paper is to improve the accuracy of magnetometer-based autonomous orbit determination during geomagnetic storms.

Design/methodology/approach

In this paper, magnetometer-based autonomous orbit determination via a measurement differencing extended Kalman filter (MDEKF) is studied. The MDEKF algorithm can effectively remove the time-correlated portion of the measurement error and thus can evidently improve the accuracy of magnetometer-based autonomous orbit determination during geomagnetic storms. Real flight data from Swarm A are used to evaluate the performance of the MDEKF algorithm presented in this study. A performance comparison between the MDEKF algorithm and an extended Kalman filter (EKF) algorithm is investigated for different geomagnetic storms and sampling intervals.

Findings

The simulation results show that the MDEKF algorithm is superior to the EKF algorithm in terms of estimation accuracy and stability with a short sampling interval during geomagnetic storms. In addition, as the size of the geomagnetic storm increases, the advantages of the MDEKF algorithm over the EKF algorithm become more obvious.

Originality/value

The algorithm in this paper can improve the real-time accuracy of magnetometer-based autonomous orbit determination during geomagnetic storms with a low computational burden and is very suitable for low-orbit micro- and nano-satellites.

Keywords

Acknowledgements

This study was granted by a laboratory fund of the Key Laboratory of Electronics and Information Technology for Space Systems, Chinese Academy of Sciences and by the National Natural Science Foundation of China (numbers 11672293). The authors were very grateful to the editors and reviewers for their valuable comments and suggestions to improve the presentation of the paper.

Citation

Cui, F., Gao, D. and Zheng, J. (2018), "Magnetometer-based autonomous orbit determination via a measurement differencing extended Kalman filter during geomagnetic storms", Aircraft Engineering and Aerospace Technology, Vol. 92 No. 3, pp. 428-439. https://doi.org/10.1108/AEAT-03-2019-0053

Publisher

:

Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited

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