Title :
Multi-satellite Combined Orbit Determination Parameterized Fusion Model and Optimal Estimation Algorithm
Author :
Zhao Deyong ; Lu Xu ; Zhang Hua
Author_Institution :
Dept. of Manage. Eng., Ordnance Eng. Coll., Shijiazhuang, China
Abstract :
The high precision denotation model of satellite orbit dynamics based on physics parameter model and mathematics model which associates sparse parameter representation with time sequence analysis, nonlinear semi-parametric combined observation model based on system error parameters modeling and non-parametric component denotation of model error, and combined orbit determination (COD) parameterized fusion model are established aiming at multi-satellite high precision COD based on bi-satellite positioning system and low earth orbiters (LEOs). Then parameters estimation algorithms of the former two kinds of models and the combined estimation algorithm of parameterized fusion model are designed. Theoretic analysis and simulated computation results show that the high precision denotation method of sparse parameters model and the optimized modeling method of observation model considering model error can improve modeling precision, and combined estimation algorithm of parameterized fusion model can synchronously ameliorate orbit determination precision ulteriorly.
Keywords :
Earth orbit; error detection; parameter estimation; satellite communication; bi-satellite positioning system; high precision denotation model; low earth orbiters; multi-satellite combined orbit determination parameterized fusion model; non-parametric component denotation; optimal estimation algorithm; parameters estimation algorithms; sparse parameter representation; system error parameters modeling; time sequence analysis; Algorithm design and analysis; Analytical models; Computational modeling; Lasers and Electro-Optics Society; Low earth orbit satellites; Mathematical model; Mathematics; Nonlinear dynamical systems; Parameter estimation; Physics; combined orbit determination; optimal estimation algorithm; parameterized fusion model;
Conference_Titel :
Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3835-8
Electronic_ISBN :
978-0-7695-3816-7
DOI :
10.1109/AICI.2009.181