The Navigation Method of Formation Flying Satellites Based on Baseline Information and Pulsars
- 10.2991/amee-17.2017.38How to use a DOI?
- formation flying satellites; X-ray pulsars; measurement of inter-satellites baseline UKF filter
The method of X-ray pulsar-based navigation can be applied to deep space exploration and earth-orbiting spacecraft navigation for its good performance in reliability and autonomy. But high-precision navigation can be hardly achieved when the input of navigation system is merely the signal of pulsars. It infers the navigation system is hardly meet the requirements of formation flying. Therefore, a new method of formation satellites autonomous navigation is proposed. The novel approach utilizes the pulsars timing observations and the measurement of inter-satellite baseline to determine the states of the satellites in a formation. The model of two satellites formation and three satellites formation is also proposed here. The corresponding unscented Kalman filters (UKF) are designed to estimate the position and velocity of the satellites. The method is performed on Matlab in the case of both two satellites formation and three satellites formation. The results show that the new method is feasible and the navigation accuracy is improved obviously. It infers that the proposed method is significant to the navigation of satellites formation.
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Kun Zhao AU - Muqing Li AU - L.P. Xu AU - Jijun Li AU - Yu Chen PY - 2017/09 DA - 2017/09 TI - The Navigation Method of Formation Flying Satellites Based on Baseline Information and Pulsars BT - Proceedings of the 2017 2nd International Conference on Automation, Mechanical and Electrical Engineering (AMEE 2017) PB - Atlantis Press SP - 183 EP - 194 SN - 2352-5401 UR - https://doi.org/10.2991/amee-17.2017.38 DO - 10.2991/amee-17.2017.38 ID - Zhao2017/09 ER -