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Data Fusion & Neural Networks, LLC STTR Phase II Award, September 2019

A STTR Phase II contract was awarded to Data Fusion & Neural Networks, LLC in September, 2019 for $750,000.0 USD from the U.S. Department of Defense and United States Air Force.

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sbir.gov/node/1860393
Is a
SBIR/STTR Awards
SBIR/STTR Awards

SBIR/STTR Award attributes

SBIR/STTR Award Recipient
Data Fusion & Neural Networks, LLC
Data Fusion & Neural Networks, LLC
0
Government Agency
U.S. Department of Defense
U.S. Department of Defense
0
Government Branch
United States Air Force
United States Air Force
0
Award Type
STTR0
Contract Number (US Government)
FA8750-19-C-10180
Award Phase
Phase II0
Award Amount (USD)
750,0000
Date Awarded
September 6, 2019
0
End Date
September 6, 2021
0
Abstract

The problem addressed in this effort is to automatically learn historical ephemeris space catalog time, position, and velocity entity track update error uncertainties (i.e., without track error covariances) and to automatically (e.g., without expert event labeling) produce: – unmodeled non-gravitational space catalog update flags – abnormal unmodeled catalog update flags with abnormality scores – categorization of similar normal unmodeled from historical behavior in new catalog unmodeled update behavior – discovered temporal relationships in historical unmodeled satellite behaviors (e.g., station keeping maneuver temporal gaps with temporal uncertainties) – missed maneuver flags with confidences and other normal unmodeled behavior relationships predicted from discovered historical temporal relationships We will improve the RDESB prototype Ephemeris Abnormal Catalog Update (eACU) which is already detecting abnormal APES ephemeris track updates on a Thought Cloud virtual machine in Bldg. 423 at Kirtland AFB. The second on-line data source is the Nebula Data Lake at the National Space Defense Center (NSDC). The Phase 2 RDESB goal is to provide threat indications and warnings left of significant unknown events in the NSDC following the same operationalization path DF&NN has for ACU implementation under an AFRL installation program.

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