Title

Aircraft Flight Data Processing And Parameter Identification With Iterative Extended Kalman Filter/Smoother And Two-Step Estimator

Author

Qiuli Yu

Advisor

Bridges, Philip D.

Committee Member

Bridges, David H.

Committee Member

Follett, Randolph F.

Committee Member

King, Robert L.

Committee Member

King, Roger L.

Date of Degree

1-1-2009

Original embargo terms

Visible to MSU Only Indefinitely||MSU Only Indefinitely||

Document Type

Dissertation - Open Access

Degree Name

Doctor of Philosophy

Abstract

Aircraft flight test data are processed by optimal estimation programs to estimate the aircraft state trajectory (3 DOF) and to identify the unknown parameters, including constant biases and scale factor of the measurement instrumentation system. The methods applied in processing aircraft flight test data are the iterative extended Kalman filter/smoother and fixed-point smoother (IEKFSFPS) method and the two-step estimator (TSE) method. The models of an aircraft flight dynamic system and measurement instrumentation system are established. The principles of IEKFSFPS and TSE methods are derived and summarized, and their algorithms are programmed with MATLAB codes. Several numerical experiments of flight data processing and parameter identification are carried out by using IEKFSFPS and TSE algorithm programs. Comparison and discussion of the simulation results with the two methods are made. The TSE+IEKFSFPS combination method is presented and proven to be effective and practical. Figures and tables of the results are presented.

URI

https://hdl.handle.net/11668/17477

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