A Decision Aid for a Surveillance Satellite Crew Shift Supervisor

The Phase I effort will focus on development methodologies for relating Surveillance Satellite Crew individual, team, and inter-team tasks, performance criteria, learning objectives, learning objective mastery, measures of effectiveness (MOEs), andmeasures of performance (MOPs)to overall Unit mission essential task lists (METLs) and satellite operations core competencies. Phase I efforts also will result in a proof-of-concept Satellite Crew Shift Supervisor decision aid demonstration.Sonalysts' proposed approach will leverage several years of Navy team training research and a substantial infrastructure of existing software developed for the Training Management Module (TMM) and Afloat Training Exercise and Management System (ATEAMS) asa starting point. Recognizing that differences between Surveillance Satellites and Navy Combat Systems are significant, there are substantial similarities in task organization and decision aid objectives that can be explored cost-effectively under thisSBIR Phase I effort.Phase II efforts will produce a full demonstration of a prototype decision aid to support a shift supervisor with a minimum of 15 subordinate crewmembers. Methods for assessing the decision aid features and interfaces to an existing satellite system orprototype will be developed. Sonalysts approach to Phase II efforts will be coordinated with Satellite Operations Training System (SOTS) common architecture and Distributed Mission Training-Space (DMT-S), Crew Trainer Emulator (CTE), or other SpaceTraining, Education and Exercise (STEDE) concepts.Development of a Surveillance Satellite Crew Shift Supervisor decision aid fits directly into the SOTS common architecture concept's Space Exercise and Training Management component and is also common withthe DMT-S structure. The framework and decision aid technology will support training management from the AETC school structure to legacy satellite systems. This research has a clear and direct impact for cost, schedule, and performance risk reduction forfuture systems such as the Space-Based Infrared Reconnaissance System (SBIRS). In addition, this effort has wider military, government, commercial, and educational application through consistency with the Office of the Secretary of Defense (OSD) AdvancedDistributed Learning (ADL) Initiative.