Novel approach to nonlinear/non-Gaussian Bayesian state estimation

Volume: 140, Issue: 2, Pages: 107 - 113
Published: Apr 1, 1993
Abstract
An algorithm, the bootstrap filter, is proposed for implementing recursive Bayesian filters. The required density of the state vector is represented as a set of random samples, which are updated and propagated by the algorithm. The method is not restricted by assumptions of linear- ity or Gaussian noise: it may be applied to any state transition or measurement model. A simula- tion example of the bearings only tracking problem is presented. This...
Paper Details
Title
Novel approach to nonlinear/non-Gaussian Bayesian state estimation
Published Date
Apr 1, 1993
Volume
140
Issue
2
Pages
107 - 113
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