Impact of Level of Autonomy on Space Systems Sizing and System-of-Systems Metrics

The objective of this study is to demonstrate how to use various modeling and analysis tools to provide support to decisions concerning the appropriate level of autonomy as a function of mission complexity. These tools evaluate design consequences and identify holistic features of space systems associated with a given level of autonomy. Space missions in the future will require an increasingly higher amount of adaptability to changing situations and the capability to per-form more complex decision-making without support from the ground. Therefore, it is interesting to quantify the impact of various levels of autonomy on space systems mass, power, volume, cost, and other requirements, as well as on holistic performance metrics. These System-of-Systems-level metrics, pertaining to the whole space mission architecture, often arise from the interaction and dependencies between systems. In this work, we demonstrate a combined use of methodologies from space systems design and System-of-Systems modeling and analysis. We select representative space systems and missions associated with different levels of autonomy, and we assess the associated technical requirements and holistic features, including complexity and expected life-cycle cost. The goal is to identify possible relationship between levels of autonomy and the corresponding sizing of space systems and resulting System-of-Systems performance, thus contributing to the ongoing dis-cussion about levels of autonomy in space systems. This will also be the first step towards future use of Machine Learning techniques to identify possible hidden relationships in this area.