… In this section, we quantify the performance of the different algorithms based on the … Because
our 1D Gaussian Estimator can find particle centers on the image plane with rms error less …

… To quantify the uncertainty of the Lagrangian evolution, we study the position errors … and
transit times in regions associated with large errors. Particular emphasis is placed on the 30-day …

… error for which we quantify a lower bound. To this aim, we use a DNS database of inertial
particle … which the error purely due to filtering is singled out removing error accumulation effects…

… 19], we focused on the error that is introduced in Lagrangian particle tracking (LPT) in LES …
by particles along their trajectory, x p (t). In particular, we quantified a lower bound for this error…

… that particle lag and intermittent seeding yield bias errors on the local average velocities. The
errors are … to minimise the calibration errors. Qureshi et al [4] investigate the measurement …

… is intimately linked with Lagrangian statistics. Recent reviews … on single particle trajectories,
and then on multiple particles. … to several times a day with a positional error of 150–1000 m. …

… of Lagrangian errors due to uncertainties in the underlying Eulerian velocity fi eld is still
lacking. The question of how to quantify Lagrangian errors versus Eulerian model errors is …

… particle per parcel) and are used to quantify the errors in simulations with larger numbers
of particles … partitioning the fluid into discrete (Lagrangian) particles that are moved (advected) …

… , can influence the error in particle positioning. The correlation process reduces random …
In order to quantify the features of the STB algorithm, the concept is applied to synthetic data …

… of errors and noise. This work addresses the problem of optimal filtering of particle tracks as
… , velocity and acceleration of observed particles. The behavior and performance of this new …