Uncertainty Evaluation: Current Status and Major Challenges

One of the basic applications of information fusion is to reduce uncertainty. The notion of position accuracy from sensor covariance reduction, confidence improvement from false alarm rejection from multimodal collections, and data filtering to limit cognitive overload are key elements of information fusion techniques to reduce uncertainty. With the advent of the various applications of information fusion, there are many instances of uncertainty from source characterization (i.e. pedigree), limiting testing for robust operations, and association of data over wide gaps in spectral, temporal, or spatial collections. This panel discussion seeks to motivate and highlight the discussion of uncertainty evaluation challenges in an information age. We envision a discussion that utilizes and expands techniques from low-level information fusion to the higher levels of information fusion. The panel is part of the ETURWG and thus has its roots in the development and support of the ISIF ETURWG. Keywords-High-level information fusion, uncertainty, situation awareness, cognition, information management, performance evaluation