Journal
INFORMATION FUSION
Volume 36, Issue -, Pages 130-148Publisher
ELSEVIER
DOI: 10.1016/j.inffus.2016.11.010
Keywords
Source estimation; Inverse modelling; Boundary tracking; Atmospheric dispersion; Optimisation; Bayesian inference; Source localisation; Dispersion modelling
Funding
- Engineering and Physical Sciences Research Council (EPSRC) [EP/K014307/1]
- MOD University Defence Research Collaboration in Signal Processing
- Future Innovation Research Fund of UNIST (Ulsan National Institute of Science and Technology) [1.160086]
- EPSRC [EP/K014307/2] Funding Source: UKRI
- Engineering and Physical Sciences Research Council [EP/K014307/2, EP/K014307/1] Funding Source: researchfish
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Understanding atmospheric transport and dispersal events has an important role in a range of scenarios. Of particular importance is aiding in emergency response after an intentional or accidental chemical, biological or radiological (CBR) release. In the event of a CBR release, it is desirable to know the current and future spatial extent of the contaminant as well as its location in order to aid decision makers in emergency response. Many dispersion phenomena may be opaque or clear, thus monitoring them using visual methods will be difficult or impossible. In these scenarios, relevant concentration sensors are required to detect the substance where they can form a static. network on the ground or be placed upon mobile platforms. This paper presents a review of techniques used to gain information about atmospheric dispersion events using static or mobile sensors. The review is concluded with a discussion on the current limitations of the state of the art and recommendations for future research. (C) 2016 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license.
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