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Rapid Discovery of Evasive Satellite Behaviors

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8750-18-C-0120
Agency Tracking Number: F17C-T02-0037
Amount: $149,999.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: AF17-CT02
Solicitation Number: 2017.0
Solicitation Year: 2017
Award Year: 2018
Award Start Date (Proposal Award Date): 2018-04-16
Award End Date (Contract End Date): 2019-04-16
Small Business Information
17150 W 95th Place
Arvada, CO 80007
United States
DUNS: 130770055
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Christopher Bowman
 (303) 469-9828
Business Contact
 Christopher Bowman
Phone: (303) 469-9828
Research Institution
 University of Texas
201 East 24th Street, Room 4.102
Austin, CO 78712
United States

 (303) 469-9828
 Nonprofit College or University

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.

* Information listed above is at the time of submission. *

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