UAV collision avoidance using sector recognition in cooperative mission to helicopters

The development of unmanned aerial aircrafts (UAVs) has made great progress recently for its broad uses in disaster rescue missions or civilian applications. UAV may be operating in joint missions with manned aircraft, mostly by helicopter. Traffic alert and collision avoidance system (TCAS) plays an important role to manned aircraft. This paper uses the concept of automatic dependent surveillance-broadcast (ADS-B) to collect aircraft data to establish collision avoidance. Based on the flight maneuvering, the proposed detection algorithm creates a sector range to cover the possible flight direction changes for UAVs and helicopters. Sector radius is calculated by speed in time. A cheese cake model is used to check the horizontal and vertical plane to conflict. Traffic advisory (TA) and resolution advisory (RA) are generated based on the overlapping area by sector recognition. In this paper, a Quasi-ADS-B flight data transceiver hardware is introduced in flight tests. The real flight experiment uses ultra-light aircrafts (ULA) to simulate helicopter and UAV in low altitude operation. From the flight experiment, the proposed TCAS for UAV and helicopter in mission airspace is verified with feasible function capability.