farshad shamlu; Abolghasem Naghash
Volume 10, Issue 2 , September 2017, , Pages 1-8
Abstract
In this study, a different approach to the prediction of satellite position is introduced.All methods are based on the Kepler’s laws of planetary motion and the orbitalperturbations such as the Earth’s oblateness, atmospheric drag, third-body perturbationand the solar-radiation pressure. ...
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In this study, a different approach to the prediction of satellite position is introduced.All methods are based on the Kepler’s laws of planetary motion and the orbitalperturbations such as the Earth’s oblateness, atmospheric drag, third-body perturbationand the solar-radiation pressure. All these perturbations are modeled and are includedseparately in the equation. However, this paper offers a new view of the prediction whichsuggests the use of artificial neural networks and observation data. The advantage of thismethod is based on the usage of observation data, so that all disturbances are taken intoaccount and there is no need to use perturbation models. For this reason, the use of theTLE as the most reachable actual data is considered. Comparison of the output of thismethod with actual data shows the accuracy of the proposed method which is very high.
D. Bustan; N. Pariz; S. K. HosseiniSani
Volume 7, Issue 3 , October 2014, , Pages 43-49
Abstract
In this paper, a new approach for orbital position prediction of satellites, is introduced. As traditional methods are based on keplerian equations of motion, orbital disturbances are uasualy neglected for simplicity. This paper, suggests artificial intelligent time series peridiction methods for orbital ...
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In this paper, a new approach for orbital position prediction of satellites, is introduced. As traditional methods are based on keplerian equations of motion, orbital disturbances are uasualy neglected for simplicity. This paper, suggests artificial intelligent time series peridiction methods for orbital position prediction of satellites. The advantage of this method is based on usage of actual data, so all disturbances are taken into account. For this reason use of TLE as the most reachable actual data is considered. Compariosion of output of this method with actual data, proofs the accuracy of proposed method.
F. Nobakht-Orsi; M. A. Sharifi; A. R. Safari
Volume 4, Issue 1 , July 2011, , Pages 15-22
Abstract
In this paper, Hilbert Huang transform (HHT) for time series analysis of the status of permanent GPS stations can be provided. Hilbert Huang transform and its, related spectrun is a new method for the analysis of nonlinear processes.This method represents not only a precision analysis in the time-frequency ...
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In this paper, Hilbert Huang transform (HHT) for time series analysis of the status of permanent GPS stations can be provided. Hilbert Huang transform and its, related spectrun is a new method for the analysis of nonlinear processes.This method represents not only a precision analysis in the time-frequency space, but also it declares the physics of the dynamic processes. This method has two speps. At the first step, the data is disintegrated into IMF elements by EMD method. At the second step Hilbert transform is applied for IMF elements and distribution of the time-frequency –Hilbert energy spectrum is then determined. In this spectrum, Location, frequency and energy defined by time events for the Hillbert transform will be reserved. So instantaneous frequency will have a major role in this method.
