| Name: | Mamta Gulati |
| Affiliation: | Thapar Institute of Engineering and Technology, Patiala |
| Conference ID : | ASI2024_799 |
| Title : | Satellite orbit modelling and prediction of orbit disintegration due to perturbations using machine learning. |
| Authors : | Mamta Gulati, Pranav Seth
|
| Authors Affiliation: | Thapar Institute of Engineers and Technology, Patiala-147004, India |
| Mode of Presentation: | Oral |
| Abstract Category : | Facilities, Technologies and Data science |
| Abstract : | Astrodynamics is a discipline that encompasses the mechanical characteristics of spacecrafts. This study focuses on the analysis of perturbation effects on the anticipated trajectory of a satellite in a low-earth orbit. Solar Radiation Pressure and Aerodynamic Drag are the two perturbation forces that have been determined through the utilization of a module constructed on a High-Performance Orbit Propagator (HPOP) and the Cannonball method. In this study, the primary Keplerian orbital characteristics were employed to analyze a simulated Low-Earth satellite orbit. Visualisation of the satellite’s trajectory and ground tracks at a designated altitude will be shown along with the comparative analysis of satellite monitoring station locations, with a primary focus on the Northern and Southern regions of the sub-continent. We shall discuss the revisit time and look angles by utilizing specific coordinates for the monitoring station locations. Other section of the current study elucidates the methodology for computing perturbation and its impact on the projected trajectory, illustrating the variance in the orbit, which is followed by the utilization of Machine Learning(ML) techniques in predicting behavioral patterns through the implementation of parametric predictive modeling. |
