Ramona Walls, CyVerse, University of Arizona, David Gaylor, University of Arizona, Vishnu Reddy, Planetary Science Institute, Roberto, Furfaro, University of Arizona, Moriba Jah, University of Arizona
Keywords: Space Object Behavior, SSA, orbital debris, ontology, data integration
Abstract:
As the population of man-made debris orbiting the Earth increases, so does the risk of damaging collisions. The Inter-Agency Space Debris Coordination Committee (IADC) has issued space debris mitigation guidelines including a key recommendation that before mission’s end, spacecraft should move far enough from GEO so as not to be an operational hazard to other objects in active missions. It can be extremely difficult to determine if a spacecraft or operator is in compliance with this guideline, as it requires prediction of future actions based upon many data types. Furthermore, there has been no comprehensive assessment of the adequacy or validity of the IADC recommendations. The EU strives for a Code of Conduct in space, the United Nations-Committee On Peaceful Uses of Outer Space (UN-COPUOS) strives for guidelines to ensure the Long Term Sustainability of Space Activities (LTSSA), the FAA is concerned with Space Traffic Management (STM), etc. If rules, policies, guidelines, and laws are put in place, how can any entity know who and what is adhering to them, when we don’t even know how to quantify and assess behavior of space objects? The University of Arizona aims to address this salient issue. As part of its new Space Object Behavioral Sciences (SOBS) initiative, the University of Arizona is developing an ontology-based system to support integration, use, and sharing of space domain data. As a first use-case, we will test the system’s ability to assess compliance with the IADC recommendation to move beyond GEO at the end of a mission as well as the adequacy and validity of recommendations. We describe the relevant data types gathered for this use-case, present a prototype ontology, and outline methods for combining semantic analysis with astrodynamics modeling. Without loss of generality, we present this method as an approach that will form the foundation of SOBS and be used to address pressing challenges in Space Situational Awareness (SSA), Orbital Safety, LTSSA, and STM.
Date of Conference: September 20-23, 2016
Track: Space Situational Awareness