Abstract
Bu çalışmada bir alçak yörünge uydusunun kinematik ve dinamik denklemleri elde edilerek döngüsel hareket için matematiksel model oluşturulmuştur. Kepler parametreleri kullanılarak bu alçak yörünge uydusunun yörünge hareket modeli elde edilmiştir. Döngüsel hareket modelden elde edilen yönelim bilgilerine gürültü eklenerek yönelim sensör verileri üretilmiştir. INS/GPS entegre navigasyon yapısı için sistem ve ölçüm modelleri elde edilerek farklı sensörlerden alınan yönelim bilgileri birleştirilmiştir. Sensör veri birleştirmede genişletilmiş Kalman filtre algoritmaları kullanılmıştır. Kestirilen yönelim bilgisi ile ölçülen ve gerçek yönelim bilgisi karşılaştırılmıştır. Sonuçlardan kestirilen yönelim bilgisinin gerçek yönelim bilgisine en yakın değer olduğu gözlemlenmiştir. Tüm çalışma MATLAB/Simulink ortamında gerçekleştirilmiştir.
Keywords
Alçak yörünge uydu matematiksel modelleme yörünge modeli döngüsel hareket modeli sensor veri birleştirme entegre navigasyon sistemi LEO satellite mathematical model orbit model of satellite attitude model of satellite sensor fusion integration navigation system
References
- F. Vatalaro, G.E. Corazza, C. Ferralli, “Analysis of LEO, MEO and GEO global mobile satellite systems in the presence of interference and fading”, IEEE Journal on Selected areas in Communication.
- C. Saunders, “The role of small satellites in military communications”, IET Seminar on Military Satellite Communication, 2013.
- Prol F. S., Ferre R. M., Saleem Z., “Position, Navigation, and Timing (PNT) Through Low Earth Orbit (LEO) Satellites, IEEE Access, 2022.
- Neinovare M., Khalife J. and Kassas Z. M., “Exploting starlink Signals for Navigation: First Results”, GNSS Conferences, 20-24 September, 2021.
- B. Gao, G. Hu, Y. Zhong, and X. Zhu, “Cubature Kalman Filter with Both Adaptability and Robustness for Tightly-coupled GNSS/INS Integration,” IEEE Sensors Journal, 2021.
- Tan N. D., Vinh T. Q., Tuyen B. T., “A new approach for Small Satellite Gyroscope and Star Tracker Fusion”, Indian Journal of Science and Technologgy, Vol 9(17), 2016
- Ilyas M., Lim J., Lee J. G., Park C. G., “Federated unscented Kalman filter design for multiple satellites formation flying in LEO”, IEEE 2008 International conference on control automation and systems
- I. Lee, H. Li, N. Hoang, and J. Lee, “Navigation system development of the underwater vehicles using the GPS/INS sensor fusion,” 14th International Conference on Control, Automation and Systems, pp. 610– 612, 2014.
- R. Song, and Y. Fang, “Vehicle state estimation for INS/GPS aided by sensors fusion and SCKF-based algorithm,” Mechanical Systems and Signal Processing, vol. 150, pp. 107315, 2021.
- Sadaf Tafazoli, Mohammad Reza Mosavi, “Performance Improvement of GPS GDOP Approximation Using Recurrent Wavelet Neural Network”, Journal of Geographic Information System, 2011, 3, 318-322
- Tahsin M., Reza T., Sultan S., Haider M. “Analysis of DOP and its Preciseness in GNSS Position Estimation “Int'l Conf. on Electrical Engineering and Information & Communication Technology (ICEEICT) 2015
- Kutlu Aykut “Design of Kalman Filter Based Attitude Determination Algorithms for a LEO Satellite and for a Satellite Attitude Control Test Setup”, METU, Master Thesis.
- Karataş Soner, “LEO SATELLITES: Dynamic Modelling, Sımulatıons and Some Nonlinear Attitude Control Techniques”, METU, Master Thesis.
- Efendioğlu Gamze, “Design of Kalman Filter based Attitute Determination and Control Algorithms for a LEO Satellite”, METU, Master Thesis.
- Kök İbrahim, “Comparison and Analysis of Attitude Control Systems of a Satellite Using Reaction Wheel Actuators” Lulea University of Technology, METU, Master Thesis.
- Groves P. “Principles of GNSS, Inertial, and Multisensor Integrated Navigation Systems”
- Karadeniz Kartal S., Leblebicioğlu M. K., Ege E., “Acousticbased navigation and system identification of an unmanned underwater vehicle”, Transaction Measurement and Control, 2019
Abstract
In this study, the mathematical model of attitude motion is obtained for low orbit sattelite (LEO) with its kinematic and dynamic equations. The mathematical model of orbit motion for LEO satellite is obtained using Kepler parameters. Sensor data are generated adding zero mean Gaussian noise to data comes from model response. These measurement data are fused using INS/GPS integration structure. Extended Kalman filter algorithm is used to sensor fusion. Compare the estimated data comes from extended Kalman filter and the actual data generated from mathematical model. It has been observed from the results that the estimated data is closest to the actual attitude data. All study is performed at the MATLAB/Simulink environment.
Keywords
LEO satellite mathematical model orbit model of satellite attitude model of satellite sensor fusion integration navigation system
References
- F. Vatalaro, G.E. Corazza, C. Ferralli, “Analysis of LEO, MEO and GEO global mobile satellite systems in the presence of interference and fading”, IEEE Journal on Selected areas in Communication.
- C. Saunders, “The role of small satellites in military communications”, IET Seminar on Military Satellite Communication, 2013.
- Prol F. S., Ferre R. M., Saleem Z., “Position, Navigation, and Timing (PNT) Through Low Earth Orbit (LEO) Satellites, IEEE Access, 2022.
- Neinovare M., Khalife J. and Kassas Z. M., “Exploting starlink Signals for Navigation: First Results”, GNSS Conferences, 20-24 September, 2021.
- B. Gao, G. Hu, Y. Zhong, and X. Zhu, “Cubature Kalman Filter with Both Adaptability and Robustness for Tightly-coupled GNSS/INS Integration,” IEEE Sensors Journal, 2021.
- Tan N. D., Vinh T. Q., Tuyen B. T., “A new approach for Small Satellite Gyroscope and Star Tracker Fusion”, Indian Journal of Science and Technologgy, Vol 9(17), 2016
- Ilyas M., Lim J., Lee J. G., Park C. G., “Federated unscented Kalman filter design for multiple satellites formation flying in LEO”, IEEE 2008 International conference on control automation and systems
- I. Lee, H. Li, N. Hoang, and J. Lee, “Navigation system development of the underwater vehicles using the GPS/INS sensor fusion,” 14th International Conference on Control, Automation and Systems, pp. 610– 612, 2014.
- R. Song, and Y. Fang, “Vehicle state estimation for INS/GPS aided by sensors fusion and SCKF-based algorithm,” Mechanical Systems and Signal Processing, vol. 150, pp. 107315, 2021.
- Sadaf Tafazoli, Mohammad Reza Mosavi, “Performance Improvement of GPS GDOP Approximation Using Recurrent Wavelet Neural Network”, Journal of Geographic Information System, 2011, 3, 318-322
- Tahsin M., Reza T., Sultan S., Haider M. “Analysis of DOP and its Preciseness in GNSS Position Estimation “Int'l Conf. on Electrical Engineering and Information & Communication Technology (ICEEICT) 2015
- Kutlu Aykut “Design of Kalman Filter Based Attitude Determination Algorithms for a LEO Satellite and for a Satellite Attitude Control Test Setup”, METU, Master Thesis.
- Karataş Soner, “LEO SATELLITES: Dynamic Modelling, Sımulatıons and Some Nonlinear Attitude Control Techniques”, METU, Master Thesis.
- Efendioğlu Gamze, “Design of Kalman Filter based Attitute Determination and Control Algorithms for a LEO Satellite”, METU, Master Thesis.
- Kök İbrahim, “Comparison and Analysis of Attitude Control Systems of a Satellite Using Reaction Wheel Actuators” Lulea University of Technology, METU, Master Thesis.
- Groves P. “Principles of GNSS, Inertial, and Multisensor Integrated Navigation Systems”
- Karadeniz Kartal S., Leblebicioğlu M. K., Ege E., “Acousticbased navigation and system identification of an unmanned underwater vehicle”, Transaction Measurement and Control, 2019
Details
| Primary Language | English |
|---|---|
| Subjects | Engineering |
| Journal Section | Articles |
| Authors | |
| Early Pub Date | December 31, 2022 |
| Publication Date | December 31, 2022 |
| Published in Issue | Year 2022 Issue: 44 |
