[1] C. Pardini and L. Anselmo, Evaluating the impact of space activities in low earth orbit, Acta Astronautica, Vol. 184, pp. 11-22, 2021.
[2] Y. Wang and P. Gurfil, Dynamical Modeling and Lifetime Analysis of Geostationary Transfer Orbits, Acta Astronautica, Vol. 128, Nov.–Dec. 2016.
[3] T.S. Kelso, Analysis Iridium 33 Cosmos 2251 Collision, Proceedings of the 19th AIAA/AAS Astrodynamics Specialist Conference, Vol. 135, 2009.
[4] A. Huang, Mastering the Game of Go with Deep Neural Networks and Tree Search, Nature, Vol. 529, No. 7587, 2016.
[5] Y. Abu-Mostafa and M. Magdon-Ismail, Learning from Data, AMLBook, Chapter 7: Neural Networks, 2015.
[6] K.-L Du and M. N. S. Swamy, Neural Networks and Statistical Learning, Springer, London, 2014.
[7] G.-B. Huang and L. Chen, Universal Approximation Using Incremental Constructive Feedforward Networks with Random Hidden Nodes, IEEE Transactions on Neural Networks, Vol. 17, No. 4, 2006.
[8] K. Williams, Prediction of Solar Activity with a Neural Network and Its Effect on Orbit Prediction, Johns Hopkins APL Technical Digest, Vol. 12, No. 4, 1991.
[9] K. P. Macpherson and A. J. Conway, Prediction of Solar and Geomagnetic Activity Data Using Neural Networks, Journal of Geophysical Research: Space Physics, Vol. 100, No. A11, 1995.
[10] D.-J. Jwo and C.-S. Chang, Neural Network Aided Adaptive Kalman Filtering for GPS Applications, 2004 IEEE International Conference on Systems, Man and Cybernetics, Vol. 4, IEEE Publ., Piscataway, NJ, 2004.
[11] C. Sánchez-Sánchez and D. Izzo, Real-Time Optimal Control via Deep Neural Networks: Study on Landing Problems,, Journal of Guidance, Control and Dynamics, Vol. 41, 2016.
[12] C. Sánchez-Sánchez and D. Izzo, Learning the Optimal State-Feedback Using Deep Networks, 2016 IEEE Symposium Series on Computational Intelligence (SSCI), IEEE Publ., Piscataway, NJ, 2016.
[13] A. Mereta and D. Izzo, Machine Learning of Optimal Low-Thrust Transfers Between Near-Earth Objects, International Conference on Hybrid Artificial Intelligence Systems, Springer, 2017.
[14] H. Peng and X. Bai, Improving Orbit Prediction Accuracy Through Supervised Machine Learning, Advances in Space Research, Vol. 61, pp. 1–30, 2018.
[15] H. Peng and X. Bai, Recovering Area-to-Mass Ratio of Resident Space Objects Through Data Mining, Acta Astronautica, Vol. 142, Jan. 2018.
[16] H. Peng and X. Bai, Limits of Machine Learning Approach on Improving Orbit Prediction Accuracy, Advanced Maui Optical and Space Surveillance Technologies (AMOS) Conference, Maui Economic Development Board, Wailea Marriott, Sept. 2017.
[17] H. Peng and X. Bai, Artificial Neural Network–Based Machine Learning Approach to Improve Orbit Prediction Accuracy, Journal of Spacecraft and Rockets, Vol. 55, pp. 1-13, 2018.
[18] J. Yu, S. Cho and J. H. Jo, KOSPAW Test bed—A Phased Array Radar for Space Situational Awareness, 2020 IEEE International Radar Conference (RADAR), pp. 786-791, 2020.
[19] M. A. Steindorfer, Space debris science at the satellite laser ranging station Graz, International Conference on Environment and Electrical Engineering, pp. 1-5, 2017.
[20] T. Schildknecht, Improved Space Object Observation Techniques using CMOS Detectors’’, 6th European Conference on Space Debris, 2013.
[21] J. Choi and J. H. Jo, Optical Tracking Data Validation and Orbit Estimation for Sparse Observations of Satellites by the OWL-Net’’, Sensors, Vol. 18, no. 6, 2018.
[22] L. Simms, Autonomous subpixel satellite track end point determination for space-based images, Applied optics, Vol. 50, 2011.
[23] D. T. Renshaw and J. A. Christine, Subpixel Localization of Isolated Edges and Streaks in Digital Images, Journal of Imaging, Vol. 6, 2020.
[24] R. Haussmann, Streak detection of space debris by a passive optical sensor, 8th European Conference on Space Debris, Vol. 8, 2021.
[25] S. Jing , A Sub-Pixel Centroid Algorithm for Star Image Based on Gaussian Distribution, Trans. Japan Soc. Aero. Space, Vol. 53, 2011.
[26] B. Jilete, OPTICAL OBSERVATIONS IN ESA’S SSA PROGRAMME, RMxAA (Serie de Conferencias), Vol. 51, pp. 139–143 ,2019.
[27] P. Gurfil, Modern Astrodynamics, Elsevier Astrodynamics Series, 1st ed., 2006.
[28] D. Vallado, Fundamentals of Astrodynamics and Applications, 4th ed., Microcosm Press, 2013.
[29] P. R. Escobal, Methods of Orbit Determination, John Wiley and Sons, Inc., New York, 1965.
[30] M. Mahooti, Initial orbit determination (Angles-only Method), Available at mathworks.com, v1.1.1.1, 2020.
[31] H. D. Curtis, Orbital Mechanics for engineering students, Elsevier Aerospace Engineering Series, 3rd ed., 2014.
[32] O. Montenbruck and E. Gill, Satellite Orbits: Models, Methods and Applications, Springer-Verlag, 2005.
[33] B. D. Abbeele, Comparing IOD methods on very short arc observations of GEO objects from the MeerLICHT telescope, Master Thesis, Delft University of Technology, 2021.
[34] F.R. Hoots and R.A. Glover, History of Analytical Orbit Modeling in the U. S. Space Surveillance System, Journal of Guidance, Control and Dynamics, AIAA, Vol. 27, No. 2, 2004.
[35] K. Wang and J Liu, Real-Time LEO Satellite Orbits Based on Batch Least-Squares Orbit Determination with Short-Term Orbit Prediction. Remote Sensing, Vol. 15, No. 133, 2023.
[36] F. Shamlu and A. Naghash, Satellite Orbit Prediction Through Observation Data and the Artificial Neural Networks. Space Science and Technology, Vol. 10, No. 2, 2017.
[37] S. Farzaneh, M.A. Sharifi and A. Abdolmaleki, Prediction of atmospheric density correction coefficients using neural networks, SEPEHR, Vol. 31, No. 121, 2022.
[38] D. Boostan, Predicting Orbital State Vector of Satellites Using Time-Series Neural Networks, Space Science and Technology, Vol. 11, No. 3, 2018.