Air Data Sensor False Fault Diagnosis in the Presence of Clear Air Turbulence

The paper discusses the challenging problem of air data false fault detection in the presence of atmospheric disturbances encountered by high-performance aircraft. Disturbances due to wind gusts and turbulences can cause a false alarm for air data failure, and detection of these is a difficult task. Flight path reconstruction environment implemented using the Extended Kalman Filtering technique with wind profile formulation is used to tackle this challenging problem for a highly manoeuvrable aircraft. Aircraft kinematic equations were used for the implementation of the state and measurement model, and the flight test data from full flight sorties were used for the air data calibration process. The proposed model is validated with real flight test data gathered with clear air turbulence for the aircraft fitted with an air-to-air refuelling probe.