Aircraft flow angles calibration via observed-based wind estimation
Aircraft Engineering and Aerospace Technology
ISSN: 0002-2667
Article publication date: 22 March 2019
Issue publication date: 15 August 2019
Abstract
Purpose
This paper aims to propose a novel approach, in which the reference data for the flow angles calibration are obtained by using measurements coming from an inertial navigation system and an air data sensor.
Design/methodology/approach
This is obtained by using the Kalman filter theory for the evaluation of the reference angle-of-attack and angle-of-sideslip.
Findings
The designed Kalman filter has been implemented in Matlab/Simulink and validated using flight data coming from two very different aircraft, the Piaggio Aerospace P1HH medium altitude long endurance unmanned aerial system and the Alenia-Aermacchi M346 Master™ transonic trainer. This paper illustrates some results where the filter satisfactory behaviour is verified by comparing the filter outputs with the data coming from high-accuracy nose-boom vanes.
Practical implications
The methodology aims to lower the calibration costs of the air data systems of an advanced aircraft.
Originality/value
The calibration of air-data systems for the evaluation of the flow angles is based on the availability of high-accuracy reference measurements of angle-of-attack and angle-of-sideslip. Typically, these are obtained by auxiliary sensors directly providing the reference angles (e.g. nose-boom vanes). The proposed methodology evaluates the reference angle-of-attack and angle-of-sideslip by analytically reconstructing them using calibrated airspeed measurements and inertial data.
Keywords
Acknowledgements
The authors wish to thank Aermacchi Company (now Leonardo S.p.A) and Piaggio Aerospace Industries S.p.A. for providing the flight tests data that have been used within this work.
Citation
Schettini, F., Di Rito, G. and Denti, E. (2019), "Aircraft flow angles calibration via observed-based wind estimation", Aircraft Engineering and Aerospace Technology, Vol. 91 No. 7, pp. 1033-1038. https://doi.org/10.1108/AEAT-06-2017-0145
Publisher
:Emerald Publishing Limited
Copyright © 2019, Emerald Publishing Limited