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Modeling the Operational Value of Data Fusion on ASW and Other Missions

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Author
Miller, Scot
Blais, Curtis
Green, John
Date
2020-10
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Abstract
The NAVAIR Mission Engineering and Analysis Department (AIR-4.0M) conducts an annual cycle of engineering, engagement, and mission-level modeling to support investment decisions. There is interest in data fusion systems, such as Minotaur. The Navy is integrating Minotaur onto the P-8A Poseidon maritime patrol aircraft and MH-60R Seahawk maritime helicopter. Minotaur integrates sensors from Poseidon and Seahawk into a comprehensive, shared, networked picture, offering increases in speed, accuracy, and memory capacity over legacy and manual data fusion systems. Fusion influences on mission effectiveness are unclear since the impact of “better” data fusion is not readily captured within existing AIR-4.0M simulations. The purpose of this study is to describe a modeling, simulation, and analysis approach for quantifying the operational effectiveness of such systems. The working hypothesis is that fusion systems add value by improving situation awareness while reducing classification and identification times. The research team identified three options for modeling such fusion: exploit the Naval Simulation System (NSS), use the Advanced Framework for Simulation, Integration, and Modeling (AFSIM), or create and/or leverage a physics-based fusion modeling approach. For FY20, the researchers recommend that using NSS is the shortest path to create fusion value understanding, and could be accomplished by modeling fusion as a “super” sensor with high probabilities of detection, classification, and identification at significant ranges. The researchers believe that this modeling challenge will continue to permeate many of the Navy’s investment decisions in the future, so for the longer term AFSIM or a physics-based modeling approach will provide greater insight.
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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.
URI
http://hdl.handle.net/10945/67927
NPS Report Number
NPS-IS-20-004
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