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Research on Non-linear Filter Methods for High Precision Satellites Orbit Determination

Author: GuoXueZuo
Tutor: ZhouHaiYin
School: National University of Defense Science and Technology
Course: Mathematics
Keywords: Nonlinear filtering algorithm Satellite orbit determination UKF Adaptive Estimation Improved UKF
CLC: TN713
Type: Master's thesis
Year: 2010
Downloads: 117
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Abstract


Satellite orbit determination satellite dynamics model constraints extracted from the observational data contain errors according to the satellite orbit information . The context of real-time determination of satellite orbit estimation problem can be seen as a nonlinear filtering problem . How to improve in the existing system hardware based on the the satellite track real-time accuracy , the usual solution is to design appropriate nonlinear filtering method based on practical engineering background . This article focused on the satellite high-precision real-time orbit determination to expand the study of nonlinear filtering method , improved UKF filtering algorithm to overcome the problems encountered in the orbit determination , in order to meet the requirements of high-precision performance indicators . In this paper, the main line of the development of a non-linear filtering , Bayes filter as a starting point from the idea of filtering to the method technology , Deep and discuss various nonlinear filtering method , summarize and chart shows the different methods links and differences between , and a brief introduction to the the LEO satellite real-time orbit determination foundation . In order to achieve the goal of high-precision , choose the method of nonlinear filtering of UKF as the main research directions. This paper presents a prediction variance matrix of the filtering process filtering and filtering gain matrix matrix Euclidean norm to describe the changes in the law , and explores the main reason for the filter divergence . On this basis , the paper mainly studies improved UKF algorithm under different circumstances . (1) For the case of the system noise and observation noise uncertainty in the kinetic model to the presence of large state noise , using a Sage-Husa the adaptive UKF Methods can be compensated to a certain extent , reduces the filtering error . (2) Second, the improvement of UKF filter gain matrix mechanics model and observation is not accurate , Kalman filtering the framework for growth in memory , such as multiple factors leading to filter divergence increase . Onboard GPS satellite orbits to determine the background of simulation experiments , simulation results show that the algorithm for filtering divergence phenomenon caused by a decline in the gain matrix good inhibition , significantly improve the precision of orbit determination .

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CLC: > Industrial Technology > Radio electronics, telecommunications technology > Basic electronic circuits > Filtering techniques,the filter
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