Referenced Items are not available for this document.
We analyze the behavior of the extended Kalman filter as a state estimator for nonlinear deterministic systems. Using the direct method of Lyapunov, we prove that under certain conditions, the extended Kalman filter is an exponential observer, i.e., the dynamics of the estimation error is exponentially stable. Furthermore, we discuss a generalization of the Kalman filter with exponential data weighting to nonlinear systems
Published in:
Signal Processing, IEEE Transactions on
(Volume:47
,
Issue:
8
)
Date of Publication: Aug 1999
- Page(s):
- 2324 - 2328
- ISSN :
- 1053-587X
- INSPEC Accession Number:
- 6323724
- Digital Object Identifier :
- 10.1109/78.774779
- Product Type:
- Journals & Magazines
- Date of Current Version :
- 06 August 2002
- Issue Date :
- Aug 1999
- Sponsored by :
- IEEE Signal Processing Society
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