Estimation and Prediction of Unmanned Aerial Vehicle Trajectories

There is serious concern about the introduction of UAV's into the National Air Space because of their potential to increase the risk of loss of separation (LOS) between aircraft. Many UAV's lack a ``sense and avoid'' (SAA) capability, i.e., they do not possess an adequate means of making the UAV pilot aware of the airspace around the platform, nor do they provide the mechanism for avoiding LOS with other aircraft. This program will address the need for LOS avoidance for UAV's operating in NAS through the development of target state estimation and trajectory prediction algorithms. Numerica proposes a research program that will focus on two critical aspects of SAA algorithms: • Development of a target state estimator that uses data up to the current time to form a robust estimate of the state vector (position, velocity, acceleration, and possibly other parameters). • Development of a target trajectory prediction algorithm. This component will take the target state estimate and probabilistically generate various possible target trajectory paths. The outcome of the research will be a complete proof-of-concept solution with a software prototype, and simulation results showing performance metrics.