Rapid Discovery of Evasive Satellite Behaviors

The DF&NN team has significant experience in delivering Space Domain Awareness tools. These tools will be applied to 2 years of GEO ephemeris data of active satellites at DF&NN. The RDESB prototype will reduce the risk in rapidly discovering the behavioral patterns of potentially evasive and/or ambiguous active resident space objects. RDESB will detect non-Keplerian behavior in ephemeris data for 2015 and then learn these normal behaviors with ANOM. ANOM application on the 2016 ephemeris will detect abnormal maneuvers, cross-tags, etc. which are tracked within Abnormality Detection Classification Viewer. The Smoking Gun tool will be extended to find temporal relationship correlations amongst these abnormal events. The ClassCat GUI will be extended to enable the user to create the Ontology-based Knowledge Graph for classification and relationship ontology labels of the abnormal signature detections to include confidences of alternative labels. The marked normal maneuvers (e.g., E/W, N/S, etc.) and relationship behaviors will be learned by sparse categorization NNs which automatically select the significant variables necessary. These sparse NNs flag 2016 abnormal and missed maneuvers and relationship precursors to create sensor tasking for increased sensor updates during times of predicted maneuvers and after these abnormality detections to achieve and maintain custody of UCTs.