Date of Award

Fall 2010

Document Type

Thesis - Open Access

Degree Name

Master of Science in Aerospace Engineering

Department

Aerospace Engineering

Committee Chair

Dr. Richard "Pat" Anderson

Committee Member

Dr. Maj Mirmirani

Committee Member

Professor Charles Eastlake

Abstract

The purpose of this study is to explore the use of an Inertial Navigation System as a primary method for measuring aircraft air flow angles in flight testing. The traditional methods used to measure air flow angles consist of sensors external to the aircraft, such as an air data boom or an angle of attack probe. The advantage of using INS to measure air flow angles would be in the simplicity of the instrumentation. All components could be fixed internally, leaving minimal external modifications to the aircraft necessary for instrumentation. This would reduce costs and instrumentation time and enable air flow angle data collection in the many aircraft already fitted with an INS. Other downfalls to external sensors are the complicated calibrations and error corrections that must be used to compensate for upwash and position error of the instruments. This study will use flight test data from the Diamond DA42 Twinstar flight test program, conducted by Embry Riddle Aeronautical University. A method was developed to estimate the air flow angles using INS and other standard flight test parameters that exclude an external air data boom. This method involves determining wind velocity in order to compute an estimate for the air flow angles. Multiple Kalman Filters use air flow angle estimates to determine essential aircraft stability derivatives. Initial values for these stability derivatives are inaccurate but, over a short period of time, the Kalman Filters are able to converge to an accurate solution, provided the necessary parameters are made observable by aircraft dynamics. The converged stability derivatives are combined with aircraft accelerations to produce accurate air flow angle measurements. These air flow angles are validated against the traditionally measured air flow angles. This enables derivation of an error prediction method for INS air flow angle measurements. The predicted error is initially high, but converges along with the estimate of the stability derivatives. The methods developed in this study are implemented in a way such that real-time estimation of the air flow angles would be possible. This method is unique by focusing on instantaneous acceleration measurements while simultaneously estimating stability derivatives.

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