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

Author

Listed:
  • Mengli Xiao
  • Yongbo Zhang
  • Zhihua Wang
  • Huimin Fu

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.

Suggested Citation

  • Mengli Xiao & Yongbo Zhang & Zhihua Wang & Huimin Fu, 2018. "Augmented robust three-stage extended Kalman filter for Mars entry-phase autonomous navigation," International Journal of Systems Science, Taylor & Francis Journals, vol. 49(1), pages 27-42, January.
    • Handle: RePEc:taf:tsysxx:v:49:y:2018:i:1:p:27-42
    DOI: 10.1080/00207721.2017.1397807
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    1. K.C. Veluvolu & M.Y. Kim & D. Lee, 2011. "Nonlinear sliding mode high-gain observers for fault estimation," International Journal of Systems Science, Taylor & Francis Journals, vol. 42(7), pages 1065-1074.
    2. Elbrous M. Jafarov, 2011. "Robust reduced-order sliding mode observer design," International Journal of Systems Science, Taylor & Francis Journals, vol. 42(4), pages 567-577.
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