SBIR-STTR Award

The Close Combat Tactical Trainer (CCTT) after-action review (AAR) system produces a standard set of statistical displays that trainers may use to debrief exercise participants. These displays are difficult to interpret and do not readily reveal to the player unit "WHAT happened" during the battle. If unit players are able to discern "WHAT happened", there are no correlating displays to provide insights into "WHY it happened." During Phase I, our focus will be on the development of trainer-friendly AAR displays that provide a direct comparison of unit performance (WHAT happened) to applicable task standards. We will also examine the feasibility of using non-network data, as well as Distributed Interactive Simulation (DIS) network data, to support the production of displays that will provide the AAR audience insights into "WHY it happened." Phase I will then examine the feasibility of using an artificial intelligence technology to support automated production of each proposed CCTT AAR display. We will recommend user interface modifications, any required hardware upgrades, and will estimate the level of effort required to develop software for the recommended functionality. During Phase II we will conduct proof-of-principle demonstrations of Phase I operational and technical concepts.

Keywords:
IMPROVED CCTT AAR DISPLAYS PEROFRMANCE MAPPED TO STANDARDS ARTIFICIAL INTELLIGENCE TECHNOLOGY

This Phase II proposal calls for the development of a command, control, communications, computers and intelligence (C41) after action review (AAR) subsystem to support exercise control functions and AAR preparations for digitized units. Trainers manning AAR workstations are overloaded and need a system that eavesdrops on player digital communications and automatically generates C4I AAR products. Trainers need an AAR system that can monitor and manage digital information by exception and alert the trainer to significant communications, miscommunications and disparities in situational awareness among the players. We developed a concept and functional requirements for an automated C4I AAR and exercise control system and named the system the Stealth AppliquT. The Stealth AppliquT will enable the trainer to selectively display the C4I screen of any key leader of the player unit and page through the various overlays and reports within the leader's digital system without the player's knowledge. The Stealth ApliquT will advise the trainer of digital messages he receives from the players and will alert the trainer to any significant player digital actions or inactions. The Stealth AppliquT will automatically prepare C4I AAR products, which will be available for the trainer's review and editing immediately after exercise termination. We envision follow-on Phase III work that will integrate the Stealth AppliquT into constructive and live simulations as well as the virtual environment. Stealth AppliquT algorithms may be extended to tactical decision aids to alert the commander or his staff when there are incongruities in situational awareness and command and control information among subordinate commanders, supporting units and higher headquarters.

Keywords:
Automated After Action Reviews Performance Mapped To Standards Digitized Units