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A Stabilized Sparse-Matrix U-D Square-Root Implementation of a Large-State Extended Kalman FilterThe full nonlinear Kalman filter sequential algorithm is, in theory, well-suited to the four-dimensional data assimilation problem in large-scale atmospheric and oceanic problems. However, it was later discovered that this algorithm can be very sensitive to computer roundoff, and that results may cease to be meaningful as time advances. Implementations of a modified Kalman filter are given.
Document ID
20060037009
Acquisition Source
Jet Propulsion Laboratory
Document Type
Preprint (Draft being sent to journal)
External Source(s)
Authors
Boggs, D.
Ghil, M.
Keppenne, C.
Date Acquired
August 23, 2013
Publication Date
March 1, 1995
Distribution Limits
Public
Copyright
Other
Keywords
data assimilation modified Kalman filter sequential algorithms

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