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.


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    Title :

    Sensor fusion approach for aircraft state estimation using inertial and air-data systems


    Contributors:
    Schettini, F. (author) / Di Rito, G. (author) / Galatolo, R. (author) / Denti, E. (author)


    Publication date :

    2016-06-01


    Size :

    4223995 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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