Detecting internal waves in laboratory scale in a stratified fluid using wavelet analysis

Since detecting waves, either surface or internal waves, is of extreme importance for researchers, they tried to identify them using physical simulation in laboratory experiments, field measurements or numerical simulations. Using Wavelet Transform instead of Fourier Transform is desirable to overcome the stationary limitation for the signal in Fourier transform or selecting objective size for short term Fourier Transform; hence, the Wavelet transform is plausible to work with nonstationary signals. Detection of internal waves are important for military concerns (e.g. sound propagation), for biological problems (e.g. oxygen penetration and available nutrients in the water column) and also for ocean dynamic issues (e.g. mixing and baroclinic velocities). In this study, having laboratory data of internal waves, the Wavelet Transform is used to detect the internal waves. The signal processing techniques have been used to fulfill this goal. It is expected to see the deficiency of Fourier Transform in detecting the nonstationary characteristics of the internal waves while the Wavelet Transform is able to do it. The results confirmed this expectation. Having no obligation to set a specific size for the window, as it is mandatory in short term Fourier Transform, is an important advantage of using Wavelet Transform to detect the internal waves.