Optimal regressors search subjected to vector autoregression of Unevenly spaced TLE series
Abstract
An iterative procedure of the parametric identification of autoregressive models with unequally spaced observations has been developed. The task of the Sich-2 spacecraft dynamics modeling using its unequally spaced TLE elements is considered. For all elements, satisfactory quality models were obtained.
References
1. JFSCC TLE Source. – Access mode via https://www.space-track.org/#Landing
2. Ivanov N. M. Ballistics and navigation of spacecraft. / N. M. Ivanov, L. N. Lysenko // M.: Drofa, 2004. - 544 p.
3. San-Juan J. F. An economic hybrid J2 analytical orbit propagator program based on SARIMA models / J. F. San-Juan, M. San-Martin, I. P´erez // Math. Probl. Eng, 2012. – 15 p.
4. San-Martin M., M´etodos de propagaci´on h´ıbridos aplicados al problema delsat´elite artificial / M. San-Martin // T´ecnicas de suavizado exponencial, University of La Rioja, 2014.
5. Ampatzis C. Machine learning techniques for approximation of objective functions in trajectory optimisation / C. Ampatzis, D. Izzo // Proceedings of the International Joint Conference on Artificial Intelligence, 2009.
6. Peng, H., Bai, X. Improving orbit prediction accuracy through supervised machine learning. / H. Peng, X. Bai // Advanced Space Research. – 2018. – № 61 (10). – 2628–2646 p.
7. Lyubushin A. A. Analysis of data from geophysical and environmental monitoring systems / A. A. Lyubushin. - M.: Science, 2007. - 228 p.
8. Sarychev A. P. Identification of parameters of systems of autoregression equations with known covariance matrices / A. P. Sarychev // International Scientific and Technical Journal “Control and Informatics Problems”. - 2012. - № 3. - 14–30 p.
9. Sarychev A. P. A study by the method of statistical tests of an iterative procedure for identifying the parameters of a system of autoregression equations / A. P. Sarychev // System Technologies. - 2014. - №3 (92). - 77–89 p.
10. Sarychev A. P. Linear autoregression based on the method of group accounting of arguments in the conditions of quasi-repeated observations / A. P. Sarychev // Artificial Intelligence. - 2015. - № 3-4 (69-70). - 105-123 p.
11. Seber J. Linear regression analysis: Per. from English / J. Seber. - M.: Mir, 1980. - 456 p.
12. Sarychev A. P. Modeling in the class of systems of autoregression equations under conditions of structural uncertainty / A. P. Sarychev // International Scientific and Technical Journal “Control and Informatics Problems”. - 2015. - № 4. - 79–103 p.
13. Sarychev A. P. Modeling of complex systems under conditions of structural uncertainty: regression and autoregression models / A. P. Sarychev. - LAP LAMBERT Academic Publishing RU, Saarbrücken, Deutschland, 2016. - 274 p.
14. Analysis of global trends in space activities, development of information-analytical and methodological support for the creation of the latest models of rocket and space technology (intermediate) in 4 volumes, volume 1 / ITM of NASU and SSAU; Head of Research A. Alpatov. - Dnepr, 2016. - 245 p. - state registration number 0116U004129. - Inv. 22 - 9/2016.
2. Ivanov N. M. Ballistics and navigation of spacecraft. / N. M. Ivanov, L. N. Lysenko // M.: Drofa, 2004. - 544 p.
3. San-Juan J. F. An economic hybrid J2 analytical orbit propagator program based on SARIMA models / J. F. San-Juan, M. San-Martin, I. P´erez // Math. Probl. Eng, 2012. – 15 p.
4. San-Martin M., M´etodos de propagaci´on h´ıbridos aplicados al problema delsat´elite artificial / M. San-Martin // T´ecnicas de suavizado exponencial, University of La Rioja, 2014.
5. Ampatzis C. Machine learning techniques for approximation of objective functions in trajectory optimisation / C. Ampatzis, D. Izzo // Proceedings of the International Joint Conference on Artificial Intelligence, 2009.
6. Peng, H., Bai, X. Improving orbit prediction accuracy through supervised machine learning. / H. Peng, X. Bai // Advanced Space Research. – 2018. – № 61 (10). – 2628–2646 p.
7. Lyubushin A. A. Analysis of data from geophysical and environmental monitoring systems / A. A. Lyubushin. - M.: Science, 2007. - 228 p.
8. Sarychev A. P. Identification of parameters of systems of autoregression equations with known covariance matrices / A. P. Sarychev // International Scientific and Technical Journal “Control and Informatics Problems”. - 2012. - № 3. - 14–30 p.
9. Sarychev A. P. A study by the method of statistical tests of an iterative procedure for identifying the parameters of a system of autoregression equations / A. P. Sarychev // System Technologies. - 2014. - №3 (92). - 77–89 p.
10. Sarychev A. P. Linear autoregression based on the method of group accounting of arguments in the conditions of quasi-repeated observations / A. P. Sarychev // Artificial Intelligence. - 2015. - № 3-4 (69-70). - 105-123 p.
11. Seber J. Linear regression analysis: Per. from English / J. Seber. - M.: Mir, 1980. - 456 p.
12. Sarychev A. P. Modeling in the class of systems of autoregression equations under conditions of structural uncertainty / A. P. Sarychev // International Scientific and Technical Journal “Control and Informatics Problems”. - 2015. - № 4. - 79–103 p.
13. Sarychev A. P. Modeling of complex systems under conditions of structural uncertainty: regression and autoregression models / A. P. Sarychev. - LAP LAMBERT Academic Publishing RU, Saarbrücken, Deutschland, 2016. - 274 p.
14. Analysis of global trends in space activities, development of information-analytical and methodological support for the creation of the latest models of rocket and space technology (intermediate) in 4 volumes, volume 1 / ITM of NASU and SSAU; Head of Research A. Alpatov. - Dnepr, 2016. - 245 p. - state registration number 0116U004129. - Inv. 22 - 9/2016.