Space Threat Automated Reasoning System (STARS)

Award Information
Department of Defense
Air Force
Award Year:
Phase I
Agency Tracking Number:
Solicitation Year:
Solicitation Topic Code:
AF 09-047
Solicitation Number:
Small Business Information
1235 South Clark Street, Suite 400, Arlington, VA, 22202
Hubzone Owned:
Minority Owned:
Woman Owned:
Principal Investigator:
Bruce Swett
Senior Engineer
(703) 414-5001
Business Contact:
Kelly McClelland
VP, Administration
(703) 414-5024
Research Institution:
Public reports of the successful test of kinetic kill anti-satellite weapons, "off the shelf" radio frequency (RF) jammers, and high-powered lasers used to blind orbiters demonstrate that both nations and non-state actors have access to effective anti-satellite offensive warfare capabilities. Also, an increasing number of nations have obtained space capabilities - a fact that means space is not only becoming more crowded, but increasingly dangerous as well. To maintain an accurate operational picture of the space-related battlespace (SRB), DECISIVE ANALYTICS Corporation will develop a modeling system that includes uncertainty and that can handle noisy and missing data. Providing such a battlespace model for space-related threats will require overcoming our current inability to: 1. Automatically create a probabilistic model of all space assets, organizations (countries, corporations, terrorists, etc.) that can impact space assets, all threat types (environmental and man-made), and geopolitical alliances, goals and influences; 2. Dynamically update the SRB model, so that it evolves over time; 3. Create predictions (inferences on the SRB model to future time-points) of Red Force courses of action (COAs) and on Blue Force space assets; and 4. Automatically create projections of the damage that predicted attacks will have on Blue Force space assets (projected impact assessment). BENEFIT: The culmination of this Phase I SBIR effort will be a demonstration of a baseline Space Threat Automated Reasoning System (STARS) prototype that can: automatically generate a model of the elements of the space-related battlespace and their relationships as they change over time. Information on the timing and time courses of multiple adversarial threats will be included in the model, which will allow the JSpOC operator to predict threats, and to have projections of the impact that specific attacks will have on friendly space-related assets. The direct benefit of the STARS engine will be vastly improved situational awareness and predictive analysis capabilities for intelligence analysts. Our primary commercialization path will be to implement STARS as a service within the SAFIRE Dynamic Counterspace Threat Indication and Warning solution for deployment in the JSIP for use by JSPOC operators. A wide variety of other commercialization opportunities exist within both the military and civilian sectors in any domain that requires the representation and prediction of complex activities using large data streams of events.

* information listed above is at the time of submission.

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