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

Majeed, M and Kar, IN (2011) Multi sensor data fusion based approach for the calibration of airdata systems. Aeronautical Journal, 115 (1164). pp. 113-122. ISSN 0001-9240

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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 wrobes 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.

Item Type:	Journal Article
Additional Information:	Copyright for this article belongs to Royal Aeronautical Society
Uncontrolled Keywords:	Multi sensor data;Airdata systems;Kalman filter;Alpha-Beta estimation algorithm
Subjects:	AERONAUTICS > Aeronautics (General) ENGINEERING > Mechanical Engineering
Division/Department:	Flight Mechanics and Control Division, Other
Depositing User:	Ms. Alphones Mary
Date Deposited:	09 Feb 2012 11:50
Last Modified:	09 Feb 2012 11:50
URI:	http://nal-ir.nal.res.in/id/eprint/10318

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