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.
- Dynamic Systems and Control Division
Spatio-Temporal Estimation of Wildfire Growth
Sharma, BR, Kumar, M, & Cohen, K. "Spatio-Temporal Estimation of Wildfire Growth." Proceedings of the ASME 2013 Dynamic Systems and Control Conference. Volume 2: Control, Monitoring, and Energy Harvesting of Vibratory Systems; Cooperative and Networked Control; Delay Systems; Dynamical Modeling and Diagnostics in Biomedical Systems; Estimation and Id of Energy Systems; Fault Detection; Flow and Thermal Systems; Haptics and Hand Motion; Human Assistive Systems and Wearable Robots; Instrumentation and Characterization in Bio-Systems; Intelligent Transportation Systems; Linear Systems and Robust Control; Marine Vehicles; Nonholonomic Systems. Palo Alto, California, USA. October 21–23, 2013. V002T25A005. ASME. https://doi.org/10.1115/DSCC2013-4022
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