期刊
IEEE CONTROL SYSTEMS LETTERS
卷 7, 期 -, 页码 1760-1765出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LCSYS.2023.3280087
关键词
Trajectory; Particle measurements; Atmospheric measurements; Autocorrelation; Optimization; Mathematical models; Differential equations; Fluid flow systems; numerical algorithms; optimization algorithms
We introduce a novel method to estimate the circulations and positions of point vortices in a 2D environment using trajectory data of passive particles affected by Gaussian noise. The method consists of two algorithms: one for calculating the vortex circulations, and the other for reconstructing the vortex trajectories. Through a hierarchy of optimization problems, involving the integration of systems of differential equations over time sub-intervals with the same amplitude defined by the autocorrelation function of the advected passive particles' trajectories, we find that accurately tracking the vortex position and determining its circulation is achievable even in the presence of noise.
We present a novel method for estimating the circulations and positions of point vortices in a two-dimensional (2D) environment using trajectory data of passive particles in the presence of Gaussian noise. The method comprises two algorithms: the first one calculates the vortex circulations, while the second one reconstructs the vortex trajectories. This reconstruction is done thanks to a hierarchy of optimization problems, involving the integration of systems of differential equations, over time sub-intervals all with the same amplitude defined by the autocorrelation function for the advected passive particles' trajectories. Our findings indicate that accurately tracking the position of vortices and determining their circulations is achievable, even when passive particle trajectories are affected by noise.
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