DocumentCode
1795254
Title
The research of satellite attitude determination algorithm based on federal filter
Author
Jing Yang ; Xiaoman Zhang
Author_Institution
Sch. of Autom. Sci. & Electr. Eng., Beihang Univ., Beijing, China
fYear
2014
fDate
8-10 Aug. 2014
Firstpage
2122
Lastpage
2127
Abstract
In order to obtain satellite attitude with better precision and reliability by using a multi-sensor satellite attitude determination system with uncertain model error, federated filter structure is adopted. The subfilter of federated filter is an improved Nonlinear filter, which is suitable for estimation of nonlinear system with uncertain model error by combining the Predictive filter and second-order divided Difference Filter (NPDF). The proposed method estimate model error and system state estimation by fusion multi-sensor information. The simulation results show that the federated filter with feedback, compared with no feedback, obtained better precision that is similar with that of centralized filter. 5 kinds of information-sharing methods are compared, Frobenius norm of estimated error variance matrix algorithm and variance matrix eigenvalue trace algorithm obtained relatively better estimation precision.
Keywords
attitude measurement; eigenvalues and eigenfunctions; nonlinear filters; sensor fusion; space vehicles; state estimation; Frobenius norm; NPDF; difference filter; estimation precision; federal filter; fusion multisensor information; information-sharing methods; multisensor satellite attitude determination system; nonlinear filter; predictive filter; satellite attitude determination algorithm; system state estimation; uncertain model error; variance matrix eigenvalue trace algorithm; Filtering algorithms; Information filters; Mathematical model; Satellites; Sun; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Guidance, Navigation and Control Conference (CGNCC), 2014 IEEE Chinese
Conference_Location
Yantai
Print_ISBN
978-1-4799-4700-3
Type
conf
DOI
10.1109/CGNCC.2014.7007503
Filename
7007503
Link To Document