Nonlinear Estimation of Flight Mode characteristics in Spin Maneuver by using Empirical Mode Decomposition Algorithm and Hilbert Transform

Identification of spin maneuver flight characteristics focused in this paper. To analyses an airplane flying quality, identification of the dynamic modes and extracting their characteristics is essential for assessment of the airplane dynamic stability and response-to-control. The paper aims to present a new method for identification of some flight modes, including natural and nonstandard modes, and extraction of their characteristics the same as instantaneous frequency and instantaneous damping ratio, directly from measurements of flight parameters in the time domain in nonlinear flight regime. Firstly, a conceptual method based on the Empirical Mode Decomposition (EMD) algorithm is proposed. The key issue of the EMD algorithm is to represent the signal as the summation of the pattern and detail parts, besides separating them from each other. by utilize the Empirical Mode Decomposition (EMD) capabilities in real-time, a local-online algorithm is introduced which estimates the signal intrinsic mode functions Secondly, by applying Hilbert- Huang transformation to IMFs obtained by EMD algorithm the flight characteristics the same as instantaneous frequency and instantaneous damping ratio for flight mode has been estimated from spin measured flight data. The results indicate the appropriate performance of the identification method in nonlinear flight regime.