This paper presents a method to estimate the
original location and the mass of an instantaneous release of hazardous material into the atmosphere. It is formulated as an inverse problem, where concentration observations from a mobile sensor are fused with meteorological information and a Gaussian puff dispersion model to characterise the
source. Bayes’ theorem is used to estimate the parameters of the release taking into account the uncertainty that exists in the dispersion parameters and meteorological variables. An
information based reward is used to guide an unmanned aerial vehicle equipped with a chemical sensor to the expected most
informative measurement locations. Simulation results compare the performance between a single mobile sensor with various amounts of static sensors.
Funding
This work was supported by the UK Engineering and Physical Sciences Research Council (EPSRC) and the Ministry of Defence (MOD) University Defence Research Collaboration in Signal Processing under the grant number EP/K014307/1.
History
School
Aeronautical, Automotive, Chemical and Materials Engineering
Department
Aeronautical and Automotive Engineering
Published in
International Conference on Robotics and Automation
Citation
HUTCHINSON, M., LIU, C. and CHEN, W-H., 2018. Information based mobile sensor planning for source term estimation of a non-continuous atmospheric release. Presented at the International Conference on Robotics and Automation (ICRA 2018), Brisbane, Australia, 21-25th May, pp. 1 - 9.
Publisher
IEEE
Version
AM (Accepted Manuscript)
Acceptance date
2018-01-12
Publication date
2018
Notes
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