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Direction/Distance/Velocity Measurements Deeply Integrated Navigation for Venus Capture Period

Published online by Cambridge University Press:  05 February 2018

Jin Liu*
Affiliation:
(College of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan 430081, People's Republic of China) (School of Instrumentation Science & Opto-electronics Engineering, Beihang University (BUAA), Beijing 100191, People's Republic of China)
Xiao-lin Ning
Affiliation:
(School of Instrumentation Science & Opto-electronics Engineering, Beihang University (BUAA), Beijing 100191, People's Republic of China)
Xin Ma
Affiliation:
(School of Instrumentation Science & Opto-electronics Engineering, Beihang University (BUAA), Beijing 100191, People's Republic of China)
Jian-cheng Fang
Affiliation:
(School of Instrumentation Science & Opto-electronics Engineering, Beihang University (BUAA), Beijing 100191, People's Republic of China)
Gang Liu
Affiliation:
(School of Instrumentation Science & Opto-electronics Engineering, Beihang University (BUAA), Beijing 100191, People's Republic of China)
*

Abstract

In the Venus capture period, it is difficult for celestial autonomous navigation to satisfy the requirement of high precision. To improve autonomous navigation performance, a Direction, Distance and Velocity (DDV) measurements deeply integrated navigation method is proposed. The “deeply” integrated navigation reflects the fact that the direction and velocity measurements suppress the Doppler effects in the pulsar signals. In the pulsar observation period, the direction and velocity measurements are utilised to compensate for Doppler effects in the pulsar signals. By these means, the residual effects can be ignored. When the direction, distance or velocity measurements are obtained, they are fused to improve the navigation performance. Simulation results demonstrate that the DDV measurements deeply integrated navigation filter converges very well, and provides highly accurate position estimation without a high quality requirement on navigation sensors.

Type
Research Article
Copyright
Copyright © The Royal Institute of Navigation 2018 

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