Artificial Neural Network Based Initial Orbit Determination for Angle-Only Data

被引：0
|
作者：
Orengul, Omer Utku [1 ]
Yenidogan, Kursat [1 ]
Sisman, Tahsin Cagri [1 ]
机构：
[1] Univ Turkish, Aeronaut Assoc, Aerosp Engn, Ankara, Turkiye
来源：
2023 10TH INTERNATIONAL CONFERENCE ON RECENT ADVANCES IN AIR AND SPACE TECHNOLOGIES, RAST | 2023年
关键词：
Initial orbit determination; artificial neural network;
D O I：
10.1109/RAST57548.2023.10197961
中图分类号：
V [航空、航天];
学科分类号：
08 ; 0825 ;
摘要：
The initial orbit determination methods are well-established for various kinds of observational data including angular, range, and range-rate data. In this work, we investigate the use of artificial neural networks (ANNs) for the initial orbit determination with angle-only observations. We used three regression algorithms of MATLAB to train ANNs predicting semi-major axis and eccentricity of equatorial orbits. The trained ANNs can predict semi-major axis values with a mean error of 0.0021% and eccentricity values with a mean error of 0.0152%. These results are obtained for 200 angular data for a given observation pass. The real promise for ANN based approach is that the raw observational data can possibly be used without any preprocessing. The results obtained in this study provide initial steps in that direction.
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页数：6
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