Improvement of a Space Surveillance Tracking Analysis Tool

Abstract: Since the beginning of space exploration, the amount of space debris has increased with thedevelopment of new space technologies. In fact, when a collision happens, new space debris aregenerated. Hence, collision risk between space debris and operational satellites rises. The purpose ofa surveillance network system consists of the detection of space objects, their classification and theirtracking. To avoid collisions, space debris objects’ orbit must be computed with sufficient accuracy. The goal of this thesis is the improvement of a pre-existing Space Surveillance and Tracking AnalysisTool. The tool is able to simulate different observation scenarios for radar or optical observer,which can be space-based or ground-based. To enhance the orbit determination, an ExtendedSquare Root Information Filter is implemented and incremented with a Smoother. Smoothers havebeen implemented for the existing filters as well, such as the Extended Kalman Filter and theUnscented Kalman Filter. A bias estimation method was added as part of the OD for all filter types.Additionally, different outlier detection methods were implemented for the automatic detection ofoutliers within the measurement data. To find the optimum orbit determination interval, differentscenarios were considered in LEO, MEO and GEO orbits. The methods were implemented anddifferent scenarios for validation will be discussed. A wide discussion on the methods implementationand their validation on different scenarios is presented, together with a comparison of the orbitdetermination results with the other filters. All the recently implemented features increase the efficiency of the tool to simulate the differentscenarios and enhance the tracking of space debris objects.