Development of data processing methods for Space Surveillance and Tracking

ESA estimated the current number of space debris to be around 129 million; collisions with orbital debris can bring failure to the mission or completely destroy the spacecraft, so space debris need to be tracked and catalogued to plan and perform collision avoidance. SPOOK is a SST software currently in development at Airbus Defence and Space GmbH in Friedrichshafen, Germany, and the objectives of the thesis were to enhance the software by improving preexisting functions and implementing new ones and to test the implemented methods and settings for Orbit Determination aiming to determine good parameter settings. The following goals have been accomplished: two functions have been improved and implemented respectively, that return output files useful for optimization of observation strategies; a function has been implemented to compute the orbit determination errors with respect to accurate ephemerides; SPOOK has been made faster in performing multiple runs of orbit determination by implementing a function to create multiple initial states vector and perform orbit determination with each one of them and by writing a Python function that launches orbit determination semi-automatically; the tests have determined that simple propagation of the state vector should be performed instead of orbit determination when the accuracy of the initial state is very high, that the Weighted Least Square method is insensitive to the accuracy of the initial state, and that Extended Kalman Filter and Unscented Kalman Filter with simulated measurements return very similar outputs if the physical model used for OD is very accurate.