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Radiation Protection Dosimetry Advance Access originally published online on November 30, 2004
Radiation Protection Dosimetry 2005 113(1):75-89; doi:10.1093/rpd/nch423
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© The Author 2004. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oupjournals.org

Analysis of a Kalman filter based method for on-line estimation of atmospheric dispersion parameters using radiation monitoring data

Martin Drews1,2, Bent Lauritzen1,* and Henrik Madsen2

1 Risø National Laboratory, DK-4000 Roskilde, Denmark
2 Informatics and Mathematical Modelling, Technical University of Denmark, DK-2800 Kgs. Lyngby, Denmark

* Corresponding author: bent.lauritzen{at}risoe.dk

A Kalman filter method is discussed for on-line estimation of radioactive release and atmospheric dispersion from a time series of off-site radiation monitoring data. The method is based on a state space approach, where a stochastic system equation describes the dynamics of the plume model parameters, and the observables are linked to the state variables through a static measurement equation. The method is analysed for three simple state space models using experimental data obtained at a nuclear research reactor. Compared to direct measurements of the atmospheric dispersion, the Kalman filter estimates are found to agree well with the measured parameters, provided that the radiation measurements are spread out in the cross-wind direction. For less optimal detector placement it proves difficult to distinguish variations in the source term and plume height; yet the Kalman filter yields consistent parameter estimates with large associated uncertainties. Improved source term assessment results, when independent estimates of the plume height can be used. Perspectives for using the method in the context of nuclear emergency management are discussed, and possible extensions to the present modelling scheme are outlined, to account for realistic accident scenarios.


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