Optimal information collection for source parameter estimation of atmospheric release phenomenon

Reza Madankan, Puneet Singla, Tarunraj Singh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations


In this research, the effect of dynamic data measurement on source parameters estimation is studied. The concept of mutual information is exploited to identify the optimal location for each sensor, while performing the dynamic data measurement to improve accuracy of estimation. For validation purposes, an advection - diffusion simulation code, SCIPUFF (Second-order Closure Integrated PUFF) is being used as a modeling testbed to study the effect of using dynamic data measurement. A Bayesian estimation framework is being used to characterize the source parameters, while data measurement is performed by mobile sensors, which are located based on the concept of maximizing the information content. As our numerical simulations show, using dynamic data measurement, based on maximum information collection, leads to considerably better estimates of source parameters.

Original languageEnglish (US)
Title of host publication2014 American Control Conference, ACC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Print)9781479932726
StatePublished - Jan 1 2014
Event2014 American Control Conference, ACC 2014 - Portland, OR, United States
Duration: Jun 4 2014Jun 6 2014

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619


Other2014 American Control Conference, ACC 2014
Country/TerritoryUnited States
CityPortland, OR

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering


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