Real-time In-situ Adaptation of Decision Parameters for Undersea Target Tracking in a Sensor Field Navy STTR FY2010.A Sol No.: Navy STTR FY2010.A Topic No.: N10A-T038 Topic Title: Real-time In-situ Adaptation of Decision Parameters for Undersea Target Tracking in a Sensor Field Proposal No.: N10A-038-0383 Firm: Intelligent Automation, Inc. 15400 Calhoun Drive Suite 400 Rockville, Maryland 20855 Contact: Renato Levy Phone: (301) 294-5241 Web Site: www.i-a-i.com Abstract: Network-centric command and control of complex military missions (e.g., anti-submarine warfare, collaborative mine hunting, etc.) calls for cost-effective designs that can dynamically tradeoff multiple conflicting objectives. Often these optimizations have to be carried out at a higher level, and the associated control directives have to be disseminated down to a distributed system, thereby, influencing its behavior. The key innovations in the proposed effort are twofold: 1) mathematical formulation and algorithm development of real-time in-situ decision-parameter adaptation for undersea target tracking in a sensor field, and 2) development of an enhanced composable cross-layer simulator for realistic undersea communication to validate the proposed algorithms. This research will be jointly conducted by Penn State University and IAI under the technical direction of Prof. Asok Ray of Penn State University. Penn State University will lead the research on formulation of multi-objective-optimization and language-measure-theoretic decision tools and the associated software development at the preliminary stage. These software tools will be developed and modified by IAI for implementation on the simulation test-bed; the software development efforts will address emulation of communication problems in the undersea network environment. Benefits: Specifically to the technologies under development in this effort, the search for an operational Pareto in complex systems is a highly common problem with very few approaches currently available. We believe that the approach presented herein, which combines aspects of mathematical analysis and practical simulations and verifications, can yield excellent results and be ported to other domains. A generic formulation of this approach can result on a viable decision support tool, and although the market is difficult to estimate since there are no substitutes for the technology, we can easily estimate in millions based on the LOE and man/hours of analysis that it replaces. Return