Augmented robust three-stage extended Kalman filter for Mars entry-phase autonomous navigation

ABSTRACT

High-precision entry navigation capability is essential for future Mars pinpoint landing missions. An augmented robust three-stage extended Kalman filter (ARThSEKF) for integrated navigation algorithm of Mars atmospheric entry with models containing parameter uncertainties and measurement errors is presented in this paper. The derivation is conducted, and the character of stability has also been analysed, in which it has been proved to be uniformly asymptotically stable. In the further simulation of Mars entry-phase navigation, ARThSEKF showed a good performance to compare with the standard extended Kalman filter. As the atmosphere density uncertainties and unknown measurement errors have been estimated precisely, the state estimation errors were controlled to a low level, of which the position and velocity were less than 100 m and 5 m/s, respectively. Therefore, ARThSEKF is suitable for dealing with non-linear systems in the presence of parameter uncertainties and unknown measurement errors, which can fulfil the requirement of future pinpoint Mars landing mission.

KEYWORDS:

• Non-linear filtering
• simulation
• Mars entry
• autonomous navigation
• augmented robust three-stage extended Kalman filter
• parameter uncertainties
• unknown measurement errors

Acknowledgments

The work described in this paper was supported by the National Basic Research Program of China (973 Program) (Grant No. 2012CB720000). The authors fully appreciate the financial support. The authors would like to thank the reviewers and the editor for many suggestions that helped improve this paper.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

National Natural Science Foundation of China [grant number 11501022].

Notes on contributors

Mengli Xiao

Mengli Xiao received her B. S. degree in mechanical engineering from Wuhan University of Science and Technology, Wuhan, China in 2013. She is currently pursuing the Ph. D. degree at School of Aeronautical Science and Engineering, Beihang University, Beijing, China. Her research interest includes navigation and nonlinear filtering.

Yongbo Zhang

Yongbo Zhang received the B. S. and Ph. D. degree in mechanical engineering from Beihang University, Beijing, China in 2006 and 2011. Since 2013, he is currently assistant professor in the School of Aeronautical Science and Engineering, Beihang University. His research interest includes navigation and nonlinear filtering, small sample techniques, reliability analysis.

Zhihua Wang

Zhihua Wang obtained her B. S. in mechanical engineering from Dalian University of Technology, Dalian, China in 2003 and the Ph. D. degree in mechanical engineering from Beihang University, Beijing, China in 2007. She is currently an associate professor in the School of Aeronautical Science and Engineering, Beihang University, Beijing. His research interest includes nonlinear filtering, generalized reliability methods.

Huimin Fu

Huimin Fu is a director of Small Sample Technology Research Center, Professor and Yangtze River Scholar in the School of Aeronautical Science and Engineering, Beihang University. His is research interest includes nonlinear filtering, navigation, reliability, small sample statistic.