The Federal Aviation Administration (FAA) averages more than 100 reports a month of interactions between unmanned aircraft systems (UAS) and commercial or private planes. For UAS to fly in civil airspace, they must be able to see, avoid, and remain “well clear” of other aircraft. With no pilot onboard to spot approaching aircraft, another sense-and-avoid (SAA) technique is required.
The Ground-Based Sense-and-Avoid (GBSAA) System enables a UAS to detect and steer clear of other aircraft. Rather than using onboard sensors to provide the location of neighboring aircraft, the GBSAA System uses existing radars to locate nearby aircraft, including those not tracked by FAA systems. Data gained from the radars are processed by unique algorithms so the system can locate and prioritize the risk from all aircraft, issue alerts to the pilots of the UAS at risk, and compute the optimal avoidance maneuver. This arrangement allows the GBSAA System to provide sense-and-avoid services to any size UAS flying within radar coverage without requiring the UAS to carry any additional equipment.
The GBSAA System provides both situational awareness and maneuver guidance, and can be used for long-duration flights. The logic uniquely assesses not only the current location and velocity of each aircraft, but also the uncertainty in these data and potential future threat aircraft maneuvers to determine the threat posed by each nearby aircraft, an optimal set of maneuvers for the UAS to regain a position of well clear, a priority-ordered list of which UAS may violate the requirement to remain well clear, and the workload challenges to the UAS pilot if the pilot changes maneuvers (for example, a rapid change between a command to turn right and a command to turn left).
One GBSAA site consists of sensors configured to accept data from up to six radars, feeding into a single processing unit to produce an integrated air picture for the region. The GBSAA operator uses two displays (one for alerts and one for traffic) to fully understand the local situation and plan ahead for potential conflicts. Each workstation then runs threat detection and maneuver logic to provide guidance for each UAS. The resulting information is relayed to the UAS pilot.
The core technology can be readily adapted to support drones engaging in hurricane damage assessments and search and rescue efforts, or applied in emerging technologies like automated air taxi services.