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.
| Translated title of the contribution | Sequential Monte Carlo methods for contour tracking of contaminant clouds |
|---|---|
| Original language | English |
| Pages (from-to) | 249 - 260 |
| Number of pages | 12 |
| Journal | Signal Processing |
| Volume | 90 (1) |
| DOIs | |
| Publication status | Published - Jan 2010 |
Bibliographical note
Publisher: Elsevier Science B.VUN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 16 Peace, Justice and Strong Institutions
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