Abstract
A classical flow-vane approach for reconstructing translational gust velocities from air data and inertial sensor measurements was improved and implemented for real-time computation. The reconstructed turbulence measurements were then included in a system identification analysis to estimate nondimensional stability and control derivatives in a longitudinal short period model using the maximum likelihood equation-error method in the frequency domain with Fourier-transform data. Flight-test results using 44 maneuvers from a subscale transport-type airplane showed that the power spectra for the reconstructed vertical gusts resembled standard Dryden or von Kármán turbulence models. Flight data in moderate and severe turbulence exhibited a decorrelation of the modeling data. In particular, pitch rate and angle-of-attack rate derivatives could both be identified from flight data about straight and level flight without special maneuvers or prior information.
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