--In asymmetric, urban scenarios, the entities of interest are individual or interrelated humans (suicide bombers, terrorists, terror cell management, etc.) and their discrete or protracted behaviors, as well as elements of the civilian physical and social infrastructure, all embedded in extensive human and civilian clutter. While the operating conditions of and the fusion algorithms for physics-based sensing systems may be adjusted to detect, identify and track humans and civilian-like objects, exclusively “hard” (physics-based) sensing systems have strong limitations due to clutter/crowds, long occlusions, etc. Humans on the other hand, while having some unique observational capabilities (for example, the abilities to judge relationships and to discern important characteristics of complex patterns) also have considerable observational limitations such as change-blindness, referentially-limited location and distance judgment, and inherent vagueness in reporting observations linguistically. New strategies and architectures for fusion systems that use all available hard and “soft” (human and informational) sources are needed to overcome these limitations.

--Dr. John Lavery is a Senior Program Manager in the Mathematics Division of the Army Research Office, where he manages a program in information fusion, urban modeling and related areas and carries out research on urban modeling. Dr. Lavery is currently leading various U.S. Army initiatives in fusion, including fusion of hard (physics-based) and soft (human, informational) data.

--Dr. James Llinas is Professor and Executive Director of the Center for Multisource Information Fusion at the State University of New York at Buffalo in the USA, where he is currently involved in three research programs related to the topic of this session.