NDLI: Kalman filter based estimation of flow states in open channels using Lagrangian sensing

Content Provider	IEEE Xplore Digital Library
Author	Rafiee, M. Qingfang Wu Bayen, A.M.
Copyright Year	2009
Description	Author affiliation: Environmental Engineering, Department of Civil and Environmental Engineering, University of California, Berkeley, 94720-1710 USA (Qingfang Wu) \|\| Department of Mechanical Engineering, University of California, Berkeley, 94710-1740 USA (Rafiee, M.) \|\| Systems Engineering, Department of Civil and Environmental Engineering, University of California, Berkeley, 94720-1710 USA (Bayen, A.M.)
Abstract	In this article, we investigate real-time estimation of flow state in open channels using the measurements obtained from Lagrangian sensors (drifters). One-dimensional Shallow Water Equations (SWE), also known as Saint-Venant equations, are used as the mathematical model for the flow. After linearizing and discretizing the PDEs using an explicit linear scheme, we construct a linear state-space model of the flow. The Kalman filter is then used to estimate the states by incorporating the measurements obtained from passive drifters. Drifters which are equipped with GPS recievers move with the flow and report their position at every time step. The position of the drifters at every time step are used to approximate the average velocity of the flow at the corresponding locations and time step. The method is implemented in simulation on a section of the Sacramento river in California using real data and the results are validated with a two-dimensional simulation of the river. Finally, the performance of the method using Lagrangian sensors is compared to the case of using Eulerian sensors.
Starting Page	8266
Ending Page	8271
File Size	957789
Page Count	6
File Format	PDF
ISBN	9781424438716
ISSN	01912216
DOI	10.1109/CDC.2009.5400661
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-12-15
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	State estimation Lagrangian functions Sea measurements Fluid flow measurement Equations Mathematical model Boundary conditions Rivers USA Councils Data assimilation
Content Type	Text
Resource Type	Article

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