Airborne Radar-Based Collision Detection and Risk Estimation for Small Unmanned Aircraft Systems

Airborne collision detection is a difficult problem due to inherent noise, errors in prediction, and challenges associated with modeling the dynamics of the intruder aircraft. Moreover, onboard limited computational resources, fast closing speeds, and unanticipated maneuvers make it challenging to detect collision without creating too many false alarms. In this paper, an innovative approach is presented to quantify likely intruder trajectories and estimate the probability of collision risk for a pair of aircraft flying at the same altitude and in close proximity given the state estimates provided by an airborne radar sensor. The proposed approach is formulated in a probabilistic framework using the reachable set concept and the statistical data contained in the uncorrelated encounter model developed by Lincoln Laboratory, Massachusetts Institute of Technology. Monte-Carlo-based simulation is used to evaluate and compare the performance of the proposed approach with linearly extrapolated collision-detectio...