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17 May 2006 Belief network-based situation assessment for air operations centers
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In dynamic environments (e.g. an Air Operations Center (AOC)), effective real-time monitoring of mission execution is highly dependent on situation awareness (SA). But whereas an individual's perception of mission progress is biased by his or her immediate tasks and environment, the combined perspectives of key individuals provides an effects-based assessment of the mission overall. Belief networks (BNs) are an ideal tool for modeling and meeting the requirements of SA: at the individual level BNs emulate a skilled human's information fusion and reasoning process in a multi-task environment in the presence of uncertainty. At the mission level, BNs are intelligently combined to yield a common operating picture. While belief networks offer significant advantages for SA in this manner, the work of defining and combining the models is difficult due to factors such as multiple-counting and conflicting reports. To address these issues, we develop a system consisting of three distinct functional elements: an off-line mechanism for rapid construction of a BN library of SA models tailored to different air combat operation situations and derived from knowledge elicitation with subject matter experts; an off-line mechanism to adapt and combine BN models that supports the ability to adjust the SA models over time and in response to novel situations not initially available or anticipated during model construction; and an on-line combination of SA models to support an enhanced SA and the ability to monitor execution status in real time and informed by and responsive to the individuals and situations involved.
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Catherine Call and Paul Gonsalves "Belief network-based situation assessment for air operations centers", Proc. SPIE 6235, Signal Processing, Sensor Fusion, and Target Recognition XV, 623513 (17 May 2006);

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