A Method for Joint Positioning of Lunar Roverbased on Federated Kalman Filter

WEI Erhu; TANG Shenquan; LIU Jiandong; DONG Cuijun

doi:10.13203/j.whugis20160137

Volume 42 Issue 10

Oct. 2017

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Geomatics and Information Science of Wuhan University > 2017 > 42(10): 1431-1437. > DOI: 10.13203/j.whugis20160137

WEI Erhu, TANG Shenquan, LIU Jiandong, DONG Cuijun. A Method for Joint Positioning of Lunar Roverbased on Federated Kalman Filter[J]. Geomatics and Information Science of Wuhan University, 2017, 42(10): 1431-1437. DOI: 10.13203/j.whugis20160137

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A Method for Joint Positioning of Lunar Roverbased on Federated Kalman Filter

1.
School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China
2.
North Information Control Institute Group Co., Ltd., Nanjing 211153, China
3.
Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai 200030, China

Funds:

The National Natural Science Foundation of China 41374012

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Author Bio:
WEI Erhu, PhD, professor, specializes in space geodesy and geodynamics. E-mail: ehwei@sgg.whu.edu.cn
Corresponding author:
TANG Shenquan, postgraduate. E-mail:tangshenquan@whu.edu.cn
Received Date: August 15, 2016
Published Date: October 04, 2017

Graphical Abstract

Abstract

Abstract

A co-localization method for lunar rover positioning based on very long baseline interferometry (VLBI) and celestial navigation systems (CNS) is presented in the paper. A federated kalman filter was utilized to implement optimal estimation of position information in order to enhance reliability and fault tolerance ability of the system. Experimentalresults calculated with measurement data from the Chang'E-3(CE-3) mission demonstrate that this method improves the positioning accuracy of the lunar rover comparing with VLBI alone or joint calculation with Least Squares method. Furthermore, this method also guarantees the reliability and stability of lunar rover positioning.
- VLBI,
- celestial navigation,
- lunar rover,
- co-localization,
- federated kalman filter

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References

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A Method for Joint Positioning of Lunar Roverbased on Federated Kalman Filter

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