Referenced Items are not available for this document.
In Parts I and II of this paper, we presented the innovations approach to linear least-squares estimation in additive white noise. In the present paper, we show how to extend this technique to the nonlinear estimation (filtering and smoothing) of non-Gaussian signals in additive white Gaussian noise. The use of the innovations allows us to obtain formulas and simple derivations that are remarkably similar to those used for the linear case thereby distinguishing clearly the essential points at which the nonlinear problem differs from the linear one.
Published in:
Automatic Control, IEEE Transactions on
(Volume:16
,
Issue:
3
)
Date of Publication: Jun 1971
- Page(s):
- 217 - 226
- ISSN :
- 0018-9286
- Digital Object Identifier :
- 10.1109/TAC.1971.1099704
- Product Type:
- Journals & Magazines
- Date of Current Version :
- 06 January 2003
- Issue Date :
- Jun 1971
- Sponsored by :
- IEEE Control Systems Society
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