Big Data Architecture and Analytics (BDAA) for Improving Combat Identification (CID) and the Common Tactical Air Picture (CTAP)
Kendall, Anthony (Tony)
Baumgartner, Wesley (Evan)
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In summary, in the past year, the research team found that the AEGIS combat system, CEC, and Link 16 are critical systems supporting combat identification (CID) for sharing data among distributed platforms, correlating and fusing data, and displaying tracks. The CID process was found to rely on the application of doctrine and the collaboration of multiple decision makers. The process was found to be significantly manual and very reliant on the experience level of analysts and decision makers. The team found that Big Data Architecture and Analytics (BDAA) shows significant potential to improving Common Tactical Air Picture (CTAP) and CID. The team also found that BDAA could be leveraged to develop advanced data models as part of data integration, data storage and retrieval; and it could support advanced automated decision aids and resource management capabilities for battle management.
PI: Dr. Ying Zhao Co-Authors: Anthony (Tony) Kendall, Bonnie Young and LCDR Wesley (Evan) Baumgartner, NPS School of GSOIS and GSEAS