Velocity fluctuation analysis via dynamic programming

A new method of calculating one-dimensional velocity fluctuations from spatially resolved density fluctuation measurements is presented. The algorithm uses vector-matching methods of dynamic programming that match structures, such as turbulent fluctuations, in two data sets. The associated time delay between data sets is estimated by determining an optimal path to transform one vector to another. This time-delay-estimation (TDE) method establishes a new benchmark for velocity analysis by achieving higher sensitivity and frequency response than previously developed methods, such as time-resolved cross correlations and wavelets. TDE has been successfully applied to beam emission spectroscopy measurements of density fluctuations to obtain poloidal flow fluctuations associated with such phenomena as the geodesic acoustic mode. The dynamic programming algorithm should allow extension to high frequency velocity fluctuations associated with underlying electrostatic potential and resulting E×B fluctuations.