Paper Info
Title
Hybrid state estimation and model-set design of invariable-structure semi-ballistic reentry vehicle.
Abstract
Multiple-model approach is one of the main streams for hybrid estimation. The difficulty of this approach to estimate the hybrid state of the semi-ballistic reentry vehicle (SBRV) is model-set design. This paper proposes a quasi-Monte Carlo model set that can ensure the estimator near-optimal in the sense of minimum mean square error (MMSE). The SBRV has a high nonlinearity and its mode is spanned by multiple parameters with known bounds. The design methods and characteristics of the quasi-Monte Carlo model set are given. The proposed model set has a higher accuracy than the model-set generated by the Monte Carlo method. The theoretical analysis and simulation results show the effectiveness and reasonability of the newly designed model set.
Year
DOI
Venue
2011
10.1007/s11432-010-4159-6
SCIENCE CHINA Information Sciences
Keywords
Field
DocType
minimum mean square error,quasi monte carlo method,quasi monte carlo,monte carlo method,design method
Monte Carlo method in statistical physics,Mathematical optimization,Monte Carlo method,Markov chain Monte Carlo,Control theory,Minimum mean square error,Hybrid Monte Carlo,Quasi-Monte Carlo method,Monte Carlo integration,Monte Carlo molecular modeling,Mathematics
Journal
Volume
Issue
ISSN
54
4
null
Citations 
PageRank 
References 
0
0.34
3
Authors
2
Name
Order
Citations
PageRank
Yongqi Liang1112.16
Chongzhao Han244671.68