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The application of time series analysis to Laser Doppler Anemometry data

Turbulence data is analysed with time series analysis. The data was measured in a shallow flow facility with Laser Doppler Anemometry (LDA). A regularly sampled signal is extracted from the irregular LDA-data using Nearest Neighbor Resampling (NNR). NNR is used because it is robust and provides an unbiased estimate of the variance. From the resampled signal a time series model is estimated. The advantage of time series modelling is that the amount of detail in the spectrum is determined automatically. Order selection can be tuned to find the most accurate model for the signal properties at a timescale of interest. The model error is used to determine whether the difference between two estimates is statistically significant.