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Index, Export and Search Archived Data for Enterprise Ground Satellite Command and Control Systems from Multiple Sources

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA9453-17-P-0409
Agency Tracking Number: F162-004-0142
Amount: $149,999.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: AF162-004
Solicitation Number: 2016.2
Solicitation Year: 2016
Award Year: 2017
Award Start Date (Proposal Award Date): 2016-12-09
Award End Date (Contract End Date): 2017-09-08
Small Business Information
1643 Hemlock Wy
Broomfield, CO 80020
United States
DUNS: 130770055
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Christopher Bowman
 President DF&NN
 (303) 469-9828
Business Contact
 Christopher Bowman
Phone: (303) 469-9828
Research Institution

DF&NN and MarkLogic will enable fast search and retrieval of big data. Detection and characterization processes both for real-time and after-the-fact analysis will maintain themselves based upon user goals and thus will not require substantial expert interaction to create and maintain rule sets. The resulting new Enterprise Ground Satellite Command and Control (E-GSCC) system will learn normal behaviors in real satellite telemetry off-line and then in real-time provide historical pattern matching and unknown abnormal pattern discovery across missions and threat locations. The E-GSCC detection and reporting processes will decide when to retrain, what data to retrain on, what to test on, and when to promote to on-line operations. Operators will monitor processes, set thresholds in real time for detection and reporting of events with supporting correlations to historical events, likely attribution, and response recommendations. We have experience in delivering these types of capabilities at TRL7 which reduces risk. We will leverage these capabilities to index, export, and search large volumes of archived data, across streams of telemetry and mission data from multiple satellites to demonstrate high performance searching for valid disparate balanced training set selection, off-line data-pattern learning, and on-line abnormal measurand correlation detection, event cause characterization, and response recommendations.

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

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