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Published in:
2007 | OriginalPaper | Chapter
A One-Step Unscented Particle Filter for Nonlinear Dynamical Systems
Authors : Nikolay Y. Nikolaev, Evgueni Smirnov
Published in: Artificial Neural Networks – ICANN 2007
Publisher: Springer Berlin Heidelberg
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This paper proposes a one-step unscented particle filter for accurate nonlinear estimation. Its design involves the elaboration of a reliable one-step unscented filter that draws state samples deterministically for doing both the time and measurement updates, without linearization of the observation model. Empirical investigations show that the one-step unscented particle filter compares favourably to relevant filters on nonlinear dynamic systems modelling.