Index, Export and Search Archived Data for Enterprise Ground Satellite Command and Control Systems from Multiple Sources
Award last edited on: 9/17/2018

Sponsored Program
Awarding Agency
Total Award Amount
Award Phase
Solicitation Topic Code
Principal Investigator
Christopher Bowman

Company Information

Data Fusion & Neural Networks LLC (AKA: Data Fusion & Neural Networks~DF&NN))

17150 West 95th Place
Arvada, CO 80007
   (720) 872-2145
Location: Single
Congr. District: 07
County: Adams

Phase I

Contract Number: FA9453-17-P-0409
Start Date: 00/00/00    Completed: 00/00/00
Phase I year
Phase I Amount
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.

Phase II

Contract Number: FA9453-18-C-0203
Start Date: 00/00/00    Completed: 00/00/00
Phase II year
Phase II Amount
The MarkLogic architecture being delivered in this effort supports multiple missions simultaneously, employs automated indexing, and supports at-scale concurrent querying with performance evaluation. The DF&NN ANOM intelligent system provides affordable data-driven and goal-driven real-time automated abnormality detection, characterization, event tracking, historical context reporting, multiple satellite status visualization, and event relationship discovery across multiple data sources. The operational payoff to JSpOC/JICSpOC is real-time automated satellite status to include on-orbit attack detection and anomaly attribution to support SSA.In Phase 2 MarkLogic provides the aggregation of heterogeneous data into a common data platform and DF&NN provides the increased personnel efficiency and cost reduction for SSA due to the new turnkey ANOM capability that will automatically determine when to retrain, what to retrain on, and when to promote to real-time operations for each satellite. The DF&NN intelligent systems have been proven at TRL7 to learn normal patterns of life to detect abnormal measurand correlations or temporal behavior in State of Health (SOH) telemetry, space weather, space catalog, and other data. DF&NN Smoking Gun tools discover unknown correlations amongst events from multiple sources. Abnormality Detection Classification Viewer (ADCV) provides historical context, ringer suppression, tailored event tracking, raw data strip charts, and abnormal correlation culprits.