Vol. 5, No. 2, 2010

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Implicit particle filters for data assimilation

Alexandre Chorin, Matthias Morzfeld and Xuemin Tu

Vol. 5 (2010), No. 2, 221–240

Implicit particle filters for data assimilation update the particles by first choosing probabilities and then looking for particle locations that assume them, guiding the particles one by one to the high probability domain. We provide a detailed description of these filters, with illustrative examples, together with new, more general, methods for solving the algebraic equations and with a new algorithm for parameter identification.

implicit sampling, data assimilation, particle filter
Mathematical Subject Classification 2000
Primary: 60G35, 62M20
Received: 24 May 2010
Accepted: 19 October 2010
Published: 11 November 2010
Alexandre Chorin
Department of Mathematics
University of California, Berkeley
Berkeley, CA 94720
United States
Matthias Morzfeld
Department of Mechanical Engineering
University of California
Berkeley, CA 94720
United States
Xuemin Tu
Department of Mathematics
University of Kansas
1460 Jayhawk Boulevard
Lawrence, KS 66045
United States