This method improves Bayesian estimation by addressing particle degeneration in state estimation using particle filters.
This paper introduces an enhanced method for progressive Bayesian estimation based on a set of deterministic samples. The information of a given measurement is gradually introduced in order to avoid particle degeneration, which is usually encountered in standard particle filters. The main contribution of this paper is to derive a new method for exploiting smoothness assumptions about the unknown underlying density function of the state.
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Uwe et al. (2016) studied this question.
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