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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/23376

Title: A review of source term estimation methods for atmospheric dispersion events using static or mobile sensors
Authors: Hutchinson, Michael
Oh, Hyondong
Chen, Wen-Hua
Keywords: Source estimation
Inverse modelling
Boundary tracking
Atmospheric dispersion
Optimisation
Bayesian inference
Source localisation
Dispersion modelling
Issue Date: 2016
Publisher: Elsevier © The Authors
Citation: HUTCHINSON, M., OH, H. and CHEN, W-H., 2016. A review of source term estimation methods for atmospheric dispersion events using static or mobile sensors. Information Fusion, 36, pp. 130-148.
Abstract: 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.
Description: This is an Open Access Article. It is published by Elsevier under the Creative Commons Attribution 4.0 International Licence (CC BY). Full details of this licence are available at http://creativecommons.org/licenses/by/4.0/.
Sponsor: This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) grant number EP/K014307/1, the MOD University Defence Research Collaboration in Signal Processing and the Future Innovation Research Fund (Project Number 1.160086) of UNIST (Ulsan National Institute of Science and Technology).
Version: Published
DOI: 10.1016/j.inffus.2016.11.010
URI: https://dspace.lboro.ac.uk/2134/23376
Publisher Link: http://dx.doi.org/10.1016/j.inffus.2016.11.010
ISSN: 1566-2535
Appears in Collections:Published Articles (Aeronautical and Automotive Engineering)

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