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INS/CNS/DNS/XNAV deep integrated navigation in a highly dynamic environment

Jintian Hu (College of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan, China)
Jin Liu (College of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan, China)
Yidi Wang (College of Aerospace Science and Engineering, National University of Defense Technology, Changsha, China)
Xiaolin Ning (School of Instrument Science and Optoelectronics Engineering, Beihang University, Beijing, China)

Aircraft Engineering and Aerospace Technology

ISSN: 0002-2667

Article publication date: 7 July 2022

Issue publication date: 2 January 2023




This study aims to address the problem of the divergence of traditional inertial navigation system (INS)/celestial navigation system (CNS)-integrated navigation for ballistic missiles. The authors introduce Doppler navigation system (DNS) and X-ray pulsar navigation (XNAV) to the traditional INS/CNS-integrated navigation system and then propose an INS/CNS/DNS/XNAV deep integrated navigation system.


DNS and XNAV can provide velocity and position information, respectively. In addition to providing velocity information directly, DNS suppresses the impact of the Doppler effect on pulsar time of arrival (TOA). A pulsar TOA with drift bias is observed during the short navigation process. To solve this problem, the pulsar TOA drift bias model is established. And the parameters of the navigation filter are optimised based on this model.


The experimental results show that the INS/CNS/DNS/XNAV deep integrated navigation can suppress the drift of the accelerometer to a certain extent to improve the precision of position and velocity determination. In addition, this integrated navigation method can reduce the required accuracy of inertial navigation, thereby reducing the cost of missile manufacturing and realising low-cost and high-precision navigation.


The velocity information provided by the DNS can suppress the pulsar TOA drift, thereby improving the positioning accuracy of the XNAV. This reflects the “deep” integration of these two navigation methods.



Funding: The author(s) disclosed receipt of the following financial support for the research, authorship and/or publication of this article: This study was supported by the National Natural Science Foundation of China (Numbers 61873196, 61772187 and 61501336).


Hu, J., Liu, J., Wang, Y. and Ning, X. (2023), "INS/CNS/DNS/XNAV deep integrated navigation in a highly dynamic environment", Aircraft Engineering and Aerospace Technology, Vol. 95 No. 1, pp. 180-189.



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