On filtering and smoothing algorithms for non-linear state estimation†
- 1 January 1970
- journal article
- research article
- Published by Taylor & Francis in International Journal of Control
- Vol. 11 (1) , 1-18
- https://doi.org/10.1080/00207177008905876
Abstract
This paper discusses a summary derivation of maximum a posteriori estimation for continuous and discrete non-linear systems. It is known that with Gaussian a priori statistics, the maximum a posteriori estimate is equivalent to an appropriate least squares fit. Filtering, fixed interval and fixed point smoothing algorithms for approximate non-linear estimation are obtained for the least squares eurve fit using ‘ running time ’ and ‘ fixed time ’ invariant embedding. Examples illustrating the use of the algorithms are presented.Keywords
This publication has 3 references indexed in Scilit:
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- Sequential Estimation of States and Parameters in Noisy Nonlinear Dynamical SystemsJournal of Basic Engineering, 1966
- ON THE FUNDAMENTAL EQUATIONS OF INVARIANT IMBEDDING, IProceedings of the National Academy of Sciences, 1961