Tracking of Multiple Contaminant Clouds

Abstract : In this paper, we address the problem of detection and tracking of multiple contaminant clouds. We develop a stochastic extension of the Gaussian puff model to characterize evolution of the average atmospheric pollutant concentration. To perform the sequential inference on this difficult problem, we propose a Markov Chain Monte Carlo (MCMC)-based particle algorithm. Numerical simulations illustrate the ability of the algorithm to detect and track multiple contaminant clouds.
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François Septier, Avishy Carmi, Simon Godsill. Tracking of Multiple Contaminant Clouds. 12th International Conference on Information Fusion, 2009. FUSION '09., Jul 2009, Seattle, WA, United States. pp.1280-1287. ⟨hal-00566637⟩

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