DOI: https://doi.org/10.18524/1810-4215.2018.31.145962

FEATURES OF KOTLIN ORBIT ESTIMATION LIBRARY

L. S. Shakun

Анотація


Since the launch of Sputnik 1, the number of objects in near-earth orbit has been constantly increasing. The growth of number of these objects increases the risk of their collisions with existing satellites and ones which will be launched, that can be accompanied by their failure or even destruction. Most space agencies and many countries have their own space surveillance networks. These networks continually measure the positions of known objects, find new ones and predict their future positions. It is necessary to know the position of the objects with an accuracy of up to the characteristic size of the operating satellites (about 10 cm or more) to prevent collisions. Today, this task can be solved only for a small number of reference satellites and only for the past.

The calculation of the objects positions in near-Earth space requires the implementation of complex models of the Earth motion and a space object using many factors affecting the final result. Some of these factors, for example, the atmospheric density and the attitude of the satellite in the space, are not well predicted by modern models and require constant refinement from observations. Ukrainian Optical Facilities for Near-Earth Space Surveillance Network (UMOS) is used to surveillance and study near-Earth space in Ukraine.

There are many practical tasks that require knowledge of the positions of the space objects. The different software solutions are being applied to solve them. All of them must implement motion models of near-Earth space objects, the Earth and the main bodies of the Solar System for their needs. Space dynamics libraries are developed to implement these models. Orekit is one of these libraries. The Kotlin Orbit Estimation Library (KOrbEstLib) is built on the features of Orekit and extends them. KOrbEstLib expands the set of input and output data types, implementing the support of a number of Ukrainian and international data formats, in particular, the formats used in the UMOS network. In addition, KOrbEstLib offers an alternative implementation for estimating the parameters of the motion model of space objects in comparison with Orekit. This paper discusses a number of implementation features of the KOrbEstLib.

Ключові слова


artificial satellite; optical observation; space dynamic software; orbit estimation; Orekit

Повний текст:

PDF (English)

Посилання


ESA’s Annual Space Environment Report, [online] Available at: (https://www.sdo.esoc.esa.int/environment_report/Space_Environment_Report_latest.pdf) [Accessed 10 October 2018].

Liou J.-C., Hall D., Krisko P. et al.: 2004, AdvSpRes, 34(5), 981.

Liou J.-C.: 2010, Orbital Debris Quarterly News, 14(1), 7 [online] Available at: (https://orbitaldebris.jsc.nasa.gov/quarterly-news/pdfs/odqnv14i1.pdf)

Liou J.-C., Matney M., a. Vavrin A. et al.: 2018, , Orbital Debris Quarterly News, 22(3), [online] Available at: (https://orbitaldebris.jsc.nasa.gov/quarterly-news/pdfs/odqnv22i3.pdf.)

Maisonobe, L., Pommier V., Parraud P.: 2008, Orekit, An accurate and efficient core layer for space flight dynamics applications, Available at: (https://orekit.org/).

NASA:, 2006, 10(2), 1 Orbital Debris Quarterly News, [online] Available at: (https://orbitaldebris.jsc.nasa.gov/quarterly-news/pdfs/odqnv10i2.pdf).

NASA: 2010, Orbital Debris Quarterly News, 14(1), 1, [online] Available at: (https://orbitaldebris.jsc.nasa.gov/quarterly-news/pdfs/odqnv14i1.pdf)

Radtke J., Stoll E.: 2016, Acta Astroautica1, 127, 482.

Shakun, L., Koshkin, N., Korobeynikova E. et al.: 2017, Odessa Astronomical Publications, 30, 242.

Shulga A., Kravchuk, S., Sybiryakova Ye. et al.: 2015, KNIT, 21(3), 74




Copyright (c) 2018 Odessa Astronomical Publications

Creative Commons License
Ця робота ліцензована Creative Commons Attribution-NonCommercial 4.0 International License.