ADS-B is a wonderful flight information and traffic reporting technology. Yet unlike legacy traffic services such as TIS-A, the ADS-B system does not have a built-in way to determine if a traffic target is a potential collision threat to your aircraft.
While the FAA’s legacy radar-based TIS-A system has computers on the ground that continuously calculate and report the threat potential to your specific aircraft, ADS-B does not. This means that any cockpit device that displays ADS-B traffic targets and generates alerts is responsible for determining if any targets are potential threats.
Dynon has developed a unique algorithm for SkyView to determine the collision probability for ADS-B traffic targets. This algorithm is much more than just a basic time and distance calculation -- our algorithm predicts the three-dimensional flight path for both your airplane and all ADS-B traffic targets that it knows about between 30 and 60 seconds into the future. If any of the flight paths present a potential collision threat SkyView will immediately generate audio and visual alerts for the pilot.
While the FAA’s legacy radar-based TIS-A system has computers on the ground that continuously calculate and report the threat potential to your specific aircraft, ADS-B does not. This means that any cockpit device that displays ADS-B traffic targets and generates alerts is responsible for determining if any targets are potential threats.
Dynon has developed a unique algorithm for SkyView to determine the collision probability for ADS-B traffic targets. This algorithm is much more than just a basic time and distance calculation -- our algorithm predicts the three-dimensional flight path for both your airplane and all ADS-B traffic targets that it knows about between 30 and 60 seconds into the future. If any of the flight paths present a potential collision threat SkyView will immediately generate audio and visual alerts for the pilot.
Nobody likes false alarms, so we also designed our algorithm to minimize nuisance alerts by automatically adapting to your aircraft’s altitude and airspeed in real-time. For example: when you are flying low and slow in the airport traffic pattern, the algorithm automatically reduces its separation parameters to account for aircraft flying in close proximity. When you are flying high and fast at cruise, the algorithm automatically increases its separation parameters to account for higher speeds and closure rates.
The result is a robust ADS-B traffic alerting system that warns you only about the traffic targets that are an actual threat to your aircraft.
Matthew Piatt