NAS Integration and Air Traffic Control (NASA NextGen Program): For the past decade, NASA has been working to develop NextGen Air Traffic Control (ATC) Management capabilities that will provide increased efficiency and throughput of the National Air Space (NAS) to meet growing system demands. The SOMAV STK module for multiple-UAS command and control directly promotes these efforts in several ways. First, it provides a high-fidelity simulation environment for testing potential ATC routing algorithms, particularly those for systems of UAS platforms. Second, our tool reduces human operator workload by pushing much of the low-level control onto the UAV platforms themselves and having the routing/coordination performed autonomously. Reducing operator burden is listed as a specific goal of within Topic A2.02 Unmanned Aircraft Systems Technology of this SBIR effort. Third, our UAS routing and coordination tool will automatically optimize separation assurance for the UAS platforms in each team, which relates to the goal of safely and seamlessly integrating UAS platforms into NextGen. Fourth, the proposed module directly promotes autonomous operation for systems of UAS platforms using machine intelligence for decision-making. Finally, the UAS coordination tool addresses NASAÔøΩs goal of advancing the state-of-the-art in autonomous navigation under uncertain conditions (e.g., collision/hazard avoidance) and cooperative task completion. UAS Communication Networks): Recent advancements (e.g., Aerial Communications Node platforms) have resulted in UAS-based aerial communications platforms that are able to provide up to 10 times more coverage than traditional ground-based communications towers, and that are able to dynamically move to address changing customer needs. There has recently been a great deal of talk about bringing these capabilities to the civilian communications sector. This forms a complex UAS route coordination problem: Given a set of UAS platforms and a dynamic set of customers that have changing bandwidth requirements and move throughout the environment (e.g., traveling from work to home, or 50,000 people being packed into a stadium on game day), how should the UAS platforms optimize their routes and coverage areas in order to optimize the total bandwidth coverage available to customers? The SOMAV module will readily address this routing and coordination problem in a way that concurrently maximizes coverage over a mobile set of customers and minimizes the total fuel consumed by the fleet of UAS communications nodes. SOMAV will provide high fidelity simulation and modeling of the entire UAS fleet and the RF communications links between the ground-based users and the UAS communications nodes including effects due to radio and antenna characteristics, weather, terrain, and communication protocol.