Study on the Orbit Prediction Errors of Space Objects Based on Historical TLE Data |
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| Institution: | 1. Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210033;2. Key Laboratory of Space Object and Debris Observation, ChineseAcademy of Sciences, Nanjing 210033;3. University of Chinese Academy of Sciences, Beijing 100049;1. School of Physics and Electronic Information Technology, Yunnan Normal University, Kunming 650500;2. Key Laboratory of High Energy Astrophysics of University of Yunnan Province, Kunming 650500;1. School of Geodesy and Geomatics, Wuhan University, 129 Luoyu Road, Wuhan 430079, China;2. The Satellite Positioning for Atmosphere, Climate and Environment (SPACE) Research Centre, School of Mathematical and Geospatial Sciences, RMIT University, GPO Box 2476, Melbourne, Victoria 3001, Australia;3. EOS Space Systems Pty. Ltd., Mount Stromlo Observatory, Cotter Road, Weston Creek, Australian Capital Territory 2611, Australia |
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| Abstract: | Two line element (TLE) released by the North American Aerospace Defense Command (NORAD) is widely used by aerospace workers, and the matched SGP4/SDP4 (Simplified General Perturbation Version 4/Simplified Deep-space Perturbation Version 4) model is used to propagate it. Nevertheless, no corresponding information about its accuracy and covariance is clearly given, thus the application of the TLE data is greatly restricted. In this paper, the determined and predicted orbits are compared to generate the orbit error data, based on the historical TLE data obtained from the Space-Track website and the SGP4/SDP4 model. By dividing different time bins, the fitting coefficients of the variation of orbit prediction error with time are given for each space object, and the characteristics of the error evolution are further discussed for the different types of orbits. The mean analytic model of the orbit prediction error evolution with time is given respectively for the four orbit types of space objects, which provides a valuable reference for extending the application of the TLE data. |
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| Keywords: | Celestial mechanics catalogs methods: data analysis methods: statistical |
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