1. Undersea Sensing
- Author
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Naval Postgraduate School (U.S.), Naval Research Program, Graduate School of Engineering and Applied Science (GSEAS), Systems Engineering (SE), Green, John M., Johnson, Bonnie, Bones, Michelle, Bunch, Leonard, Fisher, Kenneth, Stone, Alex, Mara, Stephanie, Naval Postgraduate School (U.S.), Naval Research Program, Graduate School of Engineering and Applied Science (GSEAS), Systems Engineering (SE), Green, John M., Johnson, Bonnie, Bones, Michelle, Bunch, Leonard, Fisher, Kenneth, Stone, Alex, and Mara, Stephanie
- Abstract
Project Summary: The primary goal of the research was to develop a reference architecture for undersea sensing based on product line principles using the tenets of the Joint Data Labs (JDL) data fusion model. The reference architecture work was completed as a capstone report (Bones, 2018). Specifically, the capstone report examined the concept of combining mobile and stationary underwater sensors into a coherent, distributive network. The project presented a baseline architecture for a data fusion system that facilitates the near real-time exchange of information from disparate sources. This architecture, in turn, provides a basis for further system development, and can guide future studies of relevant data/information fusion concepts and technologies for applications to anti-submarine warfare (ASW) and mine warfare. The study used the unique approach of inverse systems engineering to design an architecture based on the ASW kill chain, and the probability of success in detecting, classifying and tracking underwater objects. The resulting probability of success was then measured against the probability of success of a human ASW operator to determine the adequacy of design. ExtendSim software was used o model and simulate the architecture to validate functional capability and improved performance over the human ASW operator. The resulting architecture can facilitate the successful integration of passive acoustic sensor information with intelligence products and timely distribution of fused data across manned and unmanned platforms. The architecture also allows for future growth into active acoustic sources, environmental data sources, non-traditional ASW sources such as radar, and electronic support measures (ESM).
- Published
- 2018