Signal noise filtering using wavelet coefficient temporal correlation techniques
Ramón Lacruz Alcaraz, Pablo García-Fogeda · AIP conference proceedings · 2020
The objective of this work is to develop a robust procedure to analyze flight data by wavelet transforms, eliminate or reduce the noise of the data and to use the filtered data to determine the aeroelastic characteristics of the aircraft such that flutter condition, limit cycle oscillations and the aircraft dynamic model from the filtered measured data. Time and frequency analysis, by the use of the Continuous Wavelet transform, is used to filter noise in signals while retaining possible nonlinear terms which might otherwise be lost. Under some basic assumptions as to the nature of noise affecting signals, a technique based on temporal correlation is implemented to reduce the presence of noise by correlating wavelet coefficients. Cleaned reconstructed time domain signals are used to compute dynamic properties of systems.