A Kalman tracker for super-resolution PIV

We describe a new super-resolution method of particle-image velocimetry (PI V) based on Kalman filtering and chi (2)-testing. Performance of the "super -resolution KC" method is evaluated by Monte-Carlo simulation and by applyi ng the method to measurements of flow fields recorded in the form of double -pulse/single-frame and single-pulse/double-frame particle images. When the images have good contrast, and depending on the intensity of the velocity gradients present in the flow, the superresolution KC method is able to ext ract valid measurements from 80 to 100% of the available image pairs. In th ese tests, the vector yield is increased by more than five times compared t o standard PIV analysis.