Integration of small telescopes with satellite tracking analytical model for space situational awareness (SSA)

The integration of ground-based optical sensors with an indigenously written satellite-tracking algorithm to verify the output of computational model is of vital importance in the emerging field of Space Situational Awareness (SSA). The term SSA is used to refer to any setup, sensory or computational, focused towards tracking the natural and man-made satellites that are orbiting the Earth. A rising number of spatial bodies, both natural and artificial in the space around Earth, primarily in the low Earth orbit (LEO), pose a serious collision threat to currently operational satellites. Moreover, SSA also gives insight about spatial population to determine the optimal altitude and inclination of an orbit for all missions under design and development. Keeping in view the importance of SSA in present and future space missions, an algorithm was developed based on SGP4 and SDP4 analytical models to convert the TLE raw data into ground tracks. A satellite-tracking algorithm was then developedfirst to model ground tracks for satellites in geostationary Earth orbit (GEO) as well as low Earth orbit (LEO) by using their Two-Line Elements (TLEs), available on the NORAD database. Moreover, the code was further analyzed using the PREDICT methodology given by David Vallado to find the corresponding azimuth and elevation angles of all the satellites in consideration. Using basic feed-forward and feedback control techniques, the azimuth-elevation readings were transferred to a small telescope (less than 1m in diameter) with the help of an Alt-Az mount and fast moving slewing mechanism. Two methods were purposed in this study to integrate the telescope to mathematical solution. The setup was verified by observing the International Space Station (ISS) Zarya module as it is visible by a naked eye. The integration of an optical sensor is vital in the generation of accurate satellite ephemerides which is the basic requirement for an effective SSA setup. In the future, image optimization algorithms can be developed to improve the quality of the optical observations and to make observations of faint space objects possible.