Article

This work presents a methodology for real-time estimation of wildland fire growth, utilizing afire growth model based on a set of partial differential equations for prediction, and harnessing concepts of space-time Kalman filtering and Proper Orthogonal Decomposition techniques towards low dimensional estimation of potentially large spatio-temporal states. The estimation framework is discussed in its criticality towards potential applications such as forest fire surveillance with unmanned systems equipped with onboard sensor suites. The effectiveness of the estimation process is evaluated numerically over fire growth data simulated using a well-established fire growth model described by coupled partial differential equations. The methodology is shown to be fairly accurate in estimating spatio-temporal process states through noise-ridden measurements for real-time deploy ability.

Creator

• Sharma, Balaji R.
• Cohen, Kelly
• Kumar, Manish

License

• All rights reserved

Submitter

Kelly Cohen

College

• Engineering and Applied Science

Department

• Aerospace Engineering and Engineering Mechanics

Date Created

• 2013-10

Journal Title

• Proceedings of the ASME Dynamic Systems and Control Conference

Language

• English

Note

• This work was part of a pilot "mediated-deposit model" where library staff found potential works, later submitted for faculty review

Digital Object Identifier (DOI)

Identifier: 10.1115/DSCC2013-4022
Link: https://doi.org/10.1115/DSCC2013-4022

This DOI link is the best way for others to cite your work.

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