High Bandwidth Communications Links Between Heterogeneous Autonomous Vehicles Using Sensor Network Modeling and Extremum Control Approaches

In future network-centric warfare environments, teams of autonomous vehicles will be deployed in a coorperative manner to conduct wide-area intelligence, surveillance and reconnaissance (ISR) missions in a tactical environment. The operational range of these survey vehicles is usually limited by the line-of-sight (LOS) and/or bandwidth constraints of the communication system. To increase the operational range and to allow real-time transmission of data back to the command station, autonomous vehicles configured with high bandwidth communication system are positioned between the command station and the survey vehicles acting as communication relay vehicles and flying sensors. This will allow the survey vehicles to transfer their data back to the command station on the move, thus improving the efficiency of the missions. In this thesis, an autopilot guidance and control algorithm was developed that will allow the relay vehicles to reposition themselves autonomously to maintain an optimal loitering flight path to maximize the quality of the communication link between the command station and survey vehicle. The main contributions of this thesis are twofold. First, a communication propagation model was developed to predict the signal-to-noise (SNR) ratio of the communication link, which is used as a reference SNR signal for the UAVs. Second, the communication model was then integrated into a feedback control loop to formulate a new real-time adaptive controller, which is based on an extremum seeking approach with a gradient-based controller, to drive the relay vehicle to an optimal loitering path using SNR as the cost function.