Fusion of Space Weather Data with Satellite Telemetry

Award Information
Department of Defense
Award Year:
Phase II
Agency Tracking Number:
Solicitation Year:
Solicitation Topic Code:
Solicitation Number:
Small Business Information
Data Fusion & Neural Networks, LLC
1643 Hemlock Wy, Broomfield, CO, -
Hubzone Owned:
Minority Owned:
Woman Owned:
Principal Investigator:
Christopher Bowman
(303) 469-9828
Business Contact:
Christopher Bowman
(303) 469-9828
Research Institution:

ABSTRACT: The DF & NN team proposes to provide automated space weather (SpWx) attribution tools to characterize abnormal events detected at operational sites using the DF & NN patented Enterprise Satellite-as-a-Sensor (E-SAS) system. The DF & NN Space Situational Awareness (SSA) fusion tools, Modern Technology Solutions Incorporated operational experience, Space Environment Technologies SpWx expertise, and Intelligent Software Solutions JSpOC Mission System (JMS) expertise provide the precise talents needed for this effort. The project will develop JMS compatible SpWx attribution capabilities including visualization, integration, and validation tools at the Battlefield Evaluation Assessment SSA Testbed (BEAST), and selected E-SAS sites. AFRL will direct the focus of the effort among the following main goals: deploy the data fusion tools in the BEAST and in E-SAS operational environments, enhance space weather drill-down visualization, validate tools on extended real data sets, add forecast capabilities to the SpWx attribution framework, integrate AFRL/RVB space weather sources and tools, provide GPS Signal-to-Noise Ratio scintillation attribution, deploy Wideband Global Services SpWx attribution at 3 SOPS, provide satellite damage assessments for DMSP, gather and fuse SpWx data from MDA"s Space Tracking and Surveillance System spacecraft, assess SpWx impacts on satellite operational capabilities, and achieve TRL 5/6 for SpWx attribution on an operational system. BENEFIT: The competitive advantage of this Data Fusion & Resource Management (DF & RM) ANOM technology is in its affordability derived from the data-driven pattern learning software, ability to automatically detect and characterize the unexpected abnormal signatures, and its extendibility/reusability derived from the Dual Node Network (DNN) DF & RM technical architecture. The data-driven core of the DF & NN ANOM software enables it to be easily applied to detect, recognize, and track abnormalities in any commercial or government system. Operational prototypes of this capability are already operating on-line at to 2 satellite operations (SOPS) sites and these ANOM tools have been applied off-line to over 100 different large to enormous real data sets for over 200 combined years of data. DF & NN has a pending patent on the ANOM technology and plans to commercialize ANOM to many DoD and commercial systems in collaboration with our Commercialization Pilot Program team member Lockheed Martin Corporation (LMC) for SOPS, cyber, Remotely Piloted Aircraft, and other LMC products). The space weather attribution, context assessment, and visualization tools delivered in this effort are extendable for characterization of fused multiple source tracks in all the above commercial applications.

* information listed above is at the time of submission.

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