MAS—A mission analysis software for collision risk quantification and impact assessment of rule-based decision-making for collision avoidance

The growing number of operational spacecraft in orbit around Earth results in an increasing operational effort for collision avoidance (COLA), particularly concerning the coordination of COLA measures. In order to cope with this increased effort, the automation of future COLA operations is therefore indispensable. The Mission Analysis Software (MAS) is a web-based application developed at the Technical University of Darmstadt within the project collision avoidance, satellite coordination assessment demonstration environment (CASCADE) which is funded by the European Space Agency (ESA). The MAS promotes a rule-based approach for the automation of COLA coordination within the space community by providing analyses based on data-driven simulations. To this end, the MAS enables satellite operators to quantify the risk related to conjunctions involving other active satellites for operational or planned missions. In addition, users of the MAS can conduct a rule analysis showing the impact of incorporating a rule-based coordination approach into operations. To achieve this, users can assemble hierarchical rule sets from pre-defined customisable rule building blocks. The MAS evaluates the operational consequences of a chosen rule set, empowering users to reach bilateral and multilateral agreements with frequently conjuncting parties. With these agreements the obligation to conduct COLA manoeuvres can be assigned automatically for future conjunctions. This approach allows for the preemptive reduction of the expected number of conjunctions enabling operators to optimise orbit parameters within their mission constraints as well as the automation of COLA coordination during operations. Through this, the MAS optimises propellant needs, mission time, and required workforce associated with COLA for space missions. This paper presents the MAS, highlighting key features developed in close collaboration with stakeholders and the European Space Agency. The workflow for utilising the MAS is briefly outlined, while the primary emphasis of the paper is on detailing the conjunction assessment approach of the MAS. For this purpose, the paper presents the uncertainty estimation model of the MAS which is designed to estimate positional uncertainties of satellites based on data from ESA’s Kelvins collision avoidance data challenge. Subsequently, the methodology of the MAS for deriving avoided and remaining risk values and estimated number of manoeuvres for a simulated mission from this uncertainty data is explained showing how operational aspects of COLA are integrated into this process. Lastly, results of the MAS are presented and validated with data from ESA’s DRAMA tool suite.