A Comparative Study of Monte-Carlo Methods for Multitarget Tracking
Résumé
In this paper, we address the problem of tracking an unknown and time varying number of targets and their states from noisy observa- tions available at discrete intervals of time. Attention has recently fo- cused on the role of simulation-based approaches, including Monte Carlo methods, in solving multitarget tracking problem, as these methods are able to perform well for nonlinear and non-Gaussian data models. In this paper, we present a comparative study of several Monte-Carlo methods in terms of estimation quality and complexity.
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