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Derivative-free Nonlinear Version of Extended Recursive Three-step Filter for State and Parameter Estimation during Mars Entry.

Authors :
Xiao, Mengli
Zhang, Yongbo
Fu, Huimin
Wang, Zhihua
Source :
Journal of Navigation. May2018, Vol. 71 Issue 3, p679-696. 18p.
Publication Year :
2018

Abstract

Parameter uncertainties which may lead to divergence of traditional Kalman filters during Mars entry are investigated in this paper. To achieve high precision navigation, a Derivative-free Nonlinear version of an Extended Recursive Three-Step Filter (DNERTSF) is introduced, which suits nonlinear systems with arbitrary parameter uncertainties. A DNERTSF can estimate the state and the parameters simultaneously, and Jacobian and Hessian calculations are not necessary for this filter. Considering the uncertainties in atmosphere density, ballistic coefficient and lift-to-drag ratio, a numerical simulation of Mars entry navigation is carried out. Compared with the standard Unscented Kalman Filter (UKF), DNERTSF can effectively reduce the adverse effects of parameter uncertainties and achieve a high navigation accuracy performance, keeping position and velocity estimation errors at a very low level. In all, the DNERTSF in this paper shows good advantages for Mars entry navigation, providing a possible application for a future Mars pinpoint landing. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03734633
Volume :
71
Issue :
3
Database :
Academic Search Index
Journal :
Journal of Navigation
Publication Type :
Academic Journal
Accession number :
129202602
Full Text :
https://doi.org/10.1017/S0373463317000935