Comparison of Gaussian particle center estimators and the achievable measurement density for particle tracking velocimetry

A series of numerical simulations were conducted to investigate the perform ance of two particle center estimation algorithms for Particle Tracking Vel ocimetry: a simple three-point Gaussian estimator and a least-square Gaussi an. The smallest position error for images with reasonable noise levels was found to be approximately 0.03 pixels for both estimators using particles with diameters of 4 pixels. As both estimators performed equally well, use of the simple three-point Gaussian algorithm is recommended because it exec utes 100 times faster than the least-square algorithm. The maximum achievab le measurement density and accuracy for the three-point Gaussian estimator were determined with a numerical simulation of an Oseen vortex. Uncertainty measures have been introduced to filter out unreliable displacement measur ements. It was found that 4 to 5 velocity vectors could be obtained within a 32 x 32 pixel area with an average displacement error of 0.1 pixels. This doubles the spatial resolution of conventional cross-correlation based Par ticle Image Velocimetry at comparable accuracy.