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Information based mobile sensor planning for source term estimation of a non-continuous atmospheric release

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conference contribution
posted on 2018-02-05, 11:15 authored by Michael Hutchinson, Cunjia LiuCunjia Liu, Wen-Hua ChenWen-Hua Chen
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

Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

ISBN

9781538630815

ISSN

2577-087X

Language

  • en

Location

Australia

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