Publication:
COTS AI/ML Technology for Data Fusion and Track Management

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Authors
Garza, Victor R.
Wood, Brian
Gallup, Shelley
Mun, Johnathan
Subjects
artificial intelligence
AI/ML
intelligence fusion
data analysis
human-machine interaction
decision aids,
Advisors
Date of Issue
2022
Date
2022
Publisher
Monterey, California: Naval Postgraduate School
Language
Abstract
Existing Artificial Intelligence and Machine Learning (AI/ML) technologies can automate the filtering and accuracy of multiple data streams into the Navy's Common Operating Picture/Common Tactical Picture (COP/CTP). However, this Commercial Off The Shelf (COTS) software is not being leveraged effectively by the US Navy, specifically, the Information Warfare (IW) community for data fusion in support of track data management and targeting. Through analysis of current COTS AI/ML technologies, we will be able to posit how to optimize AI/ML software for accurate track data and disparate data source (such as GEOINT, radar data sets, and other imagery) fusion. We expect to find by completing a thorough analysis of track data and data sources input into AI/ML to fuse this informational data quickly and provide the most current/accurate intelligence. We will be able to proffer recommendations on how this all will be successfully accomplished. Additionally, the ROI of newly developed intelligence AI/ML technology (COP/CTP) will be evaluated. Once this research has been accomplished, specific improvements to various AI/ML algorithms for optimization may be examined and integration of any evaluated technology found during ROI research will be added.
Type
Poster
Description
NPS NRP Project Poster
Department
Information Sciences (IS)
Organization
Naval Research Program (NRP)
Identifiers
NPS Report Number
Sponsors
Commander, Naval Information Forces (COMNAVIFOR)
U.S. Fleet Forces Command (USFF)
Funder
This research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrp
Chief of Naval Operations (CNO)
Format
Citation
Distribution Statement
Approved for public release. Distribution is unlimited. 
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
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