Spectral analysis algorithms for the laser velocimeter - A comparative study

Abstract

Conventional methods of computing spectra require constant sampling rates and therefore must be modified to accommodate the randomly sampled data from the laser yelocimeter. Four approaches that provide estimates of the power spectra from randomly sampled data are evaluated with respect to accuracy and computational speed. Simulated data of varying spectral content are used as input. An estimate of the correlation function that resolves the random time distribution into equidistant time intervals provides the best compromise between computational speed and accuracy for laser velocimeter data.