Many techniques have been developed in order to obtain spectral density function from randomly sampled data, such as the computation of a slotted autocovariance function. Nevertheless, one may be interested in obtaining more information from laser Doppler signals than a spectral content, using more or less complex computations that can be easily conducted with an evenly sampled signal. That is the reason why reconstructing an evenly sampled signal from the original LDV data is of interest. The ability of a wavelet-based technique to reconstruct the signal with respect to statistical properties of the original one is explored, and spectral content of the reconstructed signal is given and compared with estimated spectral density function obtained through classical slotting technique. Furthermore, LDV signals taken from a screeching jet are reconstructed in order to perform spectral and bispectral analysis, showing the ability of the technique in recovering accurate information’s with only few LDV samples.
Experiments in Fluids – Springer Journals
Published: Oct 28, 2011
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