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A novel technique is introduced to increase the precision and robustness of time-resolved particle image velocimetry (TR-PIV) measurements. The innovative element of the technique is the linear combination of the correlation signal computed at different separation time intervals. The domain of the correlation signal resulting from different temporal separations is matched via homothetic transformation prior to the averaging of the correlation maps. The resulting ensemble-averaged correlation function features a significantly higher signal-to-noise ratio and a more precise velocity estimation due to the evaluation of a larger particle image displacement. The method relies on a local optimization of the observation time between snapshots taking into account the local out-of-plane motion, continuum deformation due to in-plane velocity gradient and acceleration errors. The performance of the pyramid correlation algorithm is assessed on a synthetically generated image sequence reproducing a three-dimensional Batchelor vortex; experiments conducted in air and water flows are used to assess the performance on time-resolved PIV image sequences. The numerical assessment demonstrates the effectiveness of the pyramid correlation technique in reducing both random and bias errors by a factor 3 and one order of magnitude, respectively. The experimental assessment yields a significant increase of signal strength indicating enhanced measurement robustness. Moreover, the amplitude of noisy fluctuations is considerably attenuated and higher precision is obtained for the evaluation of time-resolved velocity and acceleration.
Sciacchitano et al. (Sat,) studied this question.