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Multi sensor data fusion based approach for the calibration of airdata systems

Published online by Cambridge University Press:  27 January 2016

M. Majeed  and
I. N. Kar
M. Majeed*
Affiliation:
Flight Mechanics and Control Division, CSIR - National Aerospace Laboratories, Bangalore, India
I. N. Kar*
Affiliation:
Department of Electrical Engineering, Indian Institute of Technology, Delhi, India
*
[email protected]
[email protected]
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Abstract

Accurate and reliable airdata systems are critical for aircraft flight control system. In this paper, both extended Kalman filter (EKF) and unscented Kalman filter (UKF) based various multi sensor data fusion methods are applied to dynamic manoeuvres with rapid variations in the aircraft motion to calibrate the angle-of-attack (AOA) and angle-of-sideslip (AOSS) and are compared. The main goal of the investigations reported is to obtain online accurate flow angles from the measured vane deflection and differential pressures from probes sensitive to flow angles even in the adverse effect of wind or turbulence. The proposed algorithms are applied to both simulated as well as flight test data. Investigations are initially made using simulated flight data that include external winds and turbulence effects. When performance of the sensor fusion methods based on both EKF and UKF are compared, UKF is found to be better. The same procedures are then applied to flight test data of a high performance fighter aircraft. The results are verified with results obtained using proven an offline method, namely, output error method (OEM) for flight-path reconstruction (FPR) using ESTIMA software package. The consistently good results obtained using sensor data fusion approaches proposed in this paper establish that these approaches are of great value for online implementations.

Type
Research Article
Information
The Aeronautical Journal , Volume 115 , Issue 1164 , February 2011 , pp. 113 - 122
Copyright
Copyright © Royal Aeronautical Society 2011

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