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...

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Bibliographic Details
Published in2016 IEEE Metrology for Aerospace (MetroAeroSpace) pp. 624 - 629
Main Authors Schettini, F., Di Rito, G., Galatolo, R., Denti, E.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2016
Subjects
Air data measurements
Aircraft
Atmospheric modeling
Global Positioning System
Kalman filter
Kalman filters
Military aircraft
Receivers
self-aligning probe
Sensor fusion
simulation
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Summary: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.
DOI:10.1109/MetroAeroSpace.2016.7573289