Integrated Data Fusion and Decision Support for Dynamic Battlespace

In the traditional DF (data fusion) and DS (decision support) systems, a decision is made upon a complete set of data is provided at a given time. Operating in a 'batch processing' mode, they usually require a transfer of a large amount of data to generateoptimal decisions. However, with the ever-increasing growth of available sensors, the use of batch mode will not be technically feasible in the near future. New DF/DS systems capable of synergistic integration with the DDBs are needed.Following the above observations, this project will develop a methodology, architecture, and selected algorithms for a Dynamic Data Fusion / Dynamic Decision Support Systems (DDF/DDSS). The proposed DDF/DDSS approach performs data flow analysis on-linewith the decision making process and interacts with a human via an advanced 3-D visual interface. It identifies bottlenecks and problems in the information flow, and based on this analysis, it generates queries/requests for information update to the DDBand information sources. The DDF/DDSS requests selective data items rather than shifting large parts of the DDB to the system input. It handles loosely-coupled data collected asynchronously at different time intervals and operatesMethodology, techniques and tools developed will be applicable to problems characterized by dynamic behavior, large dimensionality of the decision space, and the use of asynchronous data sources. Specific applications include: intelligence monitoring;network and distributed computer systems monitoring; portfolio risk monitoring and arbitrage trading; computer-aided corporate management; industrial production control; data mining applied to complex distributed systems. Commercialization effort willprepare/evaluate: product specification, market analysis, competitive analysis, nature of competition, opportunities, strategy, financing options, sales and marketing.