Two-stage parametric identification procedure to predict satellite orbital motion
Abstract
The paper presents a new step-by-step procedure for constructing a navigation satellite motion model. At the first stage of the procedure, the parameters of the radiation pressure model are estimated using the maximum likelihood method. The statistic estimator based on the continuous-discrete adaptive unscented Kalman filter is proposed for the solar radiation model parameters estimation. Step-by-step scheme of filtering algorithm used for the software development are given. At the second stage, the parameters of the unaccounted perturbations model are estimated based on the results of residual differences measurements. The obtained results lead to significant improvement of prediction quality of the satellite trajectory.
Keywords
Maximum likelihood method; parametric identification; satellite orbital motion model; solar radiation model; unscented Kalman filter;
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PDFDOI: http://doi.org/10.11591/ijece.v12i5.pp5348-5354
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International Journal of Electrical and Computer Engineering (IJECE)
p-ISSN 2088-8708, e-ISSN 2722-2578
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).