The space system environment is complex, with many nonlinear constraints and independent agencies which are often stovepiped. Many of today’s Air Force satellites are susceptible to anomalies with no standardized procedures or technologies in place to detect these anomalies and discriminate them from other non-related anomalous conditions. In addition, procedures to assess the impacts of these potential anomalies are ad-hoc at best. There has been a focus in recent years towards applying data fusion technologies for the detection, discrimination, and assessment of space system threats. These research efforts correspond to levels 0, 1, and 2 of the Joint Directors Laboratory (JDL) data fusion model. The next level of this model is mission impact assessment. Mission impact assessment seeks to determine the effects of space system threats and needs to be more sophisticated than simple checklist-based courses of action in service today because multiple simultaneous events may necessitate non-linear combinations of time-phased responses.
In addition, automated mission impact assessment should significantly reduce the time needed to appropriately respond during periods of space warfare. What is needed is the development ofalgorithms and a framework for mission impact assessment for known space system threats. The framework must be robust enough to allow exercising multiple what-if scenarios as well as allowing for the integration of existing software components. A key component is the validation of the mission impact outcomes through performance metrics. The Air Force requires an architecture that perform mission impact assessment with particular emphasis on scalability and accuracy.