Sensor Fusion Approach for Aircraft State Estimation using Inertial and Air-Data Systems

This paper describes a Kalman filter that integrates the measurements coming from inertial system, GPS receiver and air data system with self-aligning probes to provide accurate sensing of the aircraft state in all the flight phases. A particular attention has been focused on the angle of attack and sideslip angle reconstruction. The evaluation of these angles becomes challenging during manoeuvres with high load factors, typical for high-performance aircraft. In these conditions, the air data elaboration accuracy is significantly lowered by the sensors' dynamics. The paper demonstrates that a relevant improvement of accuracy can be obtained in both high and low frequency range, and specific tests campaign has been carried out with a simulation platform including the flight simulator of a light military jet trainer.