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Autonomous navigation algorithm based on AUKF filter about fusion of geomagnetic and sunlight directions

Bing Hua (College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing, China)
Zhiwen Zhang (College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing, China)
Yunhua Wu (College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing, China)
Zhiming Chen (College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing, China)

International Journal of Intelligent Computing and Cybernetics

ISSN: 1756-378X

Article publication date: 18 July 2018

Issue publication date: 8 October 2018

129

Abstract

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.

Keywords

Acknowledgements

This work was partially supported by the National Natural Science Foundation of China (No. 61673208), and the National Key Research and Development Plan (No. 2016YFB0500901).

Citation

Hua, B., Zhang, Z., Wu, Y. and Chen, Z. (2018), "Autonomous navigation algorithm based on AUKF filter about fusion of geomagnetic and sunlight directions", International Journal of Intelligent Computing and Cybernetics, Vol. 11 No. 4, pp. 471-485. https://doi.org/10.1108/IJICC-07-2017-0087

Publisher

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Emerald Publishing Limited

Copyright © 2018, Emerald Publishing Limited

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