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

被引:11
作者
Xiao, Mengli [1 ]
Zhang, Yongbo [1 ]
Wang, Zhihua [1 ]
Fu, Huimin [1 ]
机构
[1] Beihang Univ, Res Ctr Small Sample Technol, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
Non-linear filtering; simulation; Mars entry; autonomous navigation; augmented robust three-stage extended Kalman filter; parameter uncertainties; unknown measurement errors; DISCRETE-TIME-SYSTEMS; UNKNOWN INPUTS; FAULT ESTIMATION; STATE ESTIMATION; DESCENT; BIAS; EXTENSION; DESIGN; DELAYS;
D O I
10.1080/00207721.2017.1397807
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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 5m/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.
引用
收藏
页码:27 / 42
页数:16
相关论文
共 41 条
[1]   Three-stage Kalman filter for state and fault estimation of linear stochastic systems with unknown inputs [J].
Ben Hmida, F. ;
Khemiri, K. ;
Ragot, J. ;
Gossa, M. .
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2012, 349 (07) :2369-2388
[2]   Mars exploration entry, descent and landing challenges [J].
Braun, Robert D. ;
Manning, Robert M. .
JOURNAL OF SPACECRAFT AND ROCKETS, 2007, 44 (02) :310-323
[3]  
Burkhart PD, 2005, AIAA GUID NAV CONTR
[4]  
Burkhart PD, 2006, AIAA GUID NAV CONTR
[5]   Uncertainty Quantification for Mars Entry, Descent, and Landing Reconstruction Using Adaptive Filtering [J].
Dutta, Soumyo ;
Braun, Robert D. ;
Karlgaard, Christopher D. .
JOURNAL OF SPACECRAFT AND ROCKETS, 2014, 51 (03) :967-977
[6]   TREATMENT OF BIAS IN RECURSIVE FILTERING [J].
FRIEDLAND, B .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1969, AC14 (04) :359-+
[7]  
Hmida F.B., 2010, MATH PROBL ENG, V1024, P629
[8]  
Hsieh C.S., 2007, P TENC IEEE REG 10 C, V12, P1
[9]   ON THE OPTIMALITY OF TWO-STAGE KALMAN FILTERING FOR SYSTEMS WITH UNKNOWN INPUTS [J].
Hsieh, Chien-Shu .
ASIAN JOURNAL OF CONTROL, 2010, 12 (04) :510-523
[10]   Optimal solution of the two-stage Kalman estimator [J].
Hsieh, CS ;
Chen, FC .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1999, 44 (01) :194-199