Measuring the Value of High Level Fusion

In most current ground force combat simulations, the operational movements and command intent of forces follow prescribed, inflexible objectives and plans. Because of this limitation, the value of advanced intelligence, surveillance, and reconnaissance (ISR) and high-level fusion is reflected only in better targeting and not in improved operational-level command and control (C2). RAND has developed an agent interaction-based constructive simulation called the Ground C4-ISR Assessment Model (GCAM) to help examine the contributions of C4-ISR to ground forces. In GCAM simulated ground force commanders make decisions on the basis of shared awareness derived from information produced by Level 1 (Identify/Correlate), Level 2 (Aggregate/Resolve), and Level 3 (Interpret/Determine/Predict) fusion processes. In this way simulated ground commanders can adapt their plans in response to perceived changes in enemy capability, activity, or intent, or to perceived changes to the battlefield environment. This paper details the representation of high-level fusion processes used in GCAM and developed with the support of the U.S. Army Model Improvement Program. Those processes are modeled using the Assistant Secretary of Defense for Networks and Information Integration (ASD-NII) Decision Support Center (DSC) Multi-INT fusion study “Knowledge Matrix” methodology. The information or knowledge added by high-level fusion and analysis of raw sensor data from multiple sources is represented in this methodology by increased information quality levels for activity, capability, and intent. This research will allow military analysts to demonstrate the utility and the relative importance of improved C2 and high-level fusion capabilities for Army and Joint forces.