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Federated Unscented Kalman Filter Design for Multiple Satellites Formation Flying in LEO

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Authors
Ilyas, Muhammad; Lim, JunKyu; Lee, Jang Gyu; Park, Chan Gook
Issue Date
2008-10
Citation
ICCAS, 2008.
Keywords
Relative dynamic modelformation flyingfederated UKFfault detection and isolation
Abstract
The main focus of this paper is to design a more accurate optimal/suboptimal fault tolerant state
estimator for relative dynamic model representing formation flying of two satellites in low earth orbit (LEO).
First of all a mathematical model describing the relative dynamic motion of two satellites in formation is derived
and next state estimation based on Kalman filter is emphasized. The measurement system comprises of a RADAR
sensor installed on the leader satellite which measures the relative position, azimuth and elevation angle of the follower
satellite with respect to reference satellite and carrier phase differential GPS (CDGPS) sensor measuring relative
position directly. We have adopted nonlinear system and measurement models and used more advanced nonlinear
filtering method called Unscented Kalman filter (UKF) in this paper in pursue of better state estimator in a nonlinear
environment. Also we are using more than one sensor to measure same state hence this becomes a multisensor data
fusion problem. We implement a federated UKF and apply fault detection and isolation (FDI) algorithms to get a fault
tolerant filter. A comparison of Unscented Kalman filter and extended Kalman filter has been made to show superior
performance of UKF.
Language
English
URI
https://hdl.handle.net/10371/10056
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College of Engineering/Engineering Practice School (공과대학/대학원)Dept. of Mechanical Aerospace Engineering (기계항공공학부)Others_기계항공공학부
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