Sequential Monte Carlo methods for contour tracking of contaminant clouds

Abstract

This paper addresses the problem of contour tracking for airborne emission of contaminant clouds. This is of particular relevance in the context of anti-terrorism and military applications. This problem is solved by estimating the contour boundary positions using a set of particle filters. The use of sequential Monte Carlo techniques enables the tracking to be performed when the measurements are noisy. The tracking results also include the estimation uncertainty. The proposed technique is illustrated for both SCIPUFF and model generated emission scenarios and simulation experiments demonstrate successful tracking throughout the tracking period for both simple and complex environments.