Real-time Calibration of Embedded Simulation for Faster than Real-time Course Of Action Analysis (COAA)

The U.S. Army is looking for technologies that better support mission planning and re-planning for forces on-the-move. Existing tools and those under development, such as the Coalition Joint Spectrum Management Planning Tool (CJSMPT), are required to provide on-the-move automated interference and de-confliction analysis in support of mission-related network operations planning amidst the uncertainties presented by forces-on-the move. These tools must also provide processes that off-load portions of the operator’s cognitive workload. The CARET (COA Analysis with Real-time Effects Toolbox) Framework prototype addresses these needs by making use of distributed agents to extract and inject real-time data into embedded simulations for use in evaluating COAs amidst real-time C4ISR effects. This framework provides the capabilities needed by the CJSMPT to consider prediction and uncertainty presented by forces on the move through COA Analysis simulations, corresponding agent-driven faster-than-real-time network analysis, real-time C4I calibrated data updates for consistently evaluating the mission and network state, and reflective cognitive agents to assist network operations planning and re-planning activities in real-time by off-loading portions of the cognitive workload. The Phase I effort has demonstrated several of these basic agents that take into account COA simulation (OneSAF), emitter databases, intelligent agents, and network models (ITM) as a proof-of-concept.