Information Filtering for Rapid Battlefield Visualization

The primary objective of the Phase I study is to develop a model-based Intelligent Information Filter and Situation Display IIFSD) for the battlefield commander. Operating in a high-tempo information-dense tactical environment, the IIFSD is envisioned as providing the commander with a means fo filtering out the ritical information needed from the mass of data available, and displaying it in a situationally-relevant fashion. The system is predicated on:1) a limited-scope computational model of the commander's situation assessment (SA) activity; 2) an SA-driven information filter acting on the input data stream;and 3) a situationally-dependent display of the filtered information. A number of enabling technologies are incorporated in the design: information filtering strategies for reducing data redundancy and inconsistency; system-theoretic models of the human decision-maker; neural network pattern recognizers; belief networks for situation assessment; and expert systems decision models. We plan to develop and demonstrate a limited-scope prototype of the IIFSD via a four task effort: 1 definition of a tactical scenario; 2) development of a limited scope cognitive model; 3) development of a model-driven information filter; and 4) implementation of an IIFCSD prototype.