NASA NTRS · 20060037011
A Reduced Dimension Static, Linearized Kalman Filter and Smoother
Abstract
An approximate Kalman filter and smoother, based on approximations of the state estimation error covariance matrix, is described. Approximations include a reduction of the effective state dimension, use of a static asymptotic error limit, and a time-invariant linearization of the dynamic model for error integration. The approximations lead to dramatic computational savings in applying estimation theory to large complex systems. Examples of use come from TOPEX/POSEIDON.
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Fukumori, I.. 1995-03-01. A Reduced Dimension Static, Linearized Kalman Filter and Smoother. https://ntrs.nasa.gov/citations/20060037011
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