Novel approach to nonlinear/non-Gaussian Bayesian state estimation

@inproceedings{Gordon1993NovelAT,
  title={Novel approach to nonlinear/non-Gaussian Bayesian state estimation},
  author={Neil J. Gordon and David Salmond and Adrian F. M. Smith},
  year={1993}
}
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 simulation includes schemes for improving the… Expand

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