Nonlinear filtering using measurements affected by stochastic, set-theoretic and association uncertainty

@article{Ristic2011NonlinearFU,
  title={Nonlinear filtering using measurements affected by stochastic, set-theoretic and association uncertainty},
  author={Branko Ristic and Amadou Gning and Lyudmila Mihaylova},
  journal={14th International Conference on Information Fusion},
  year={2011},
  pages={1-8}
}
The problem is sequential Bayesian detection and estimation of nonlinear dynamic stochastic systems using measurements affected by three sources of uncertainty: stochastic, set-theoretic and data association uncertainty. Following Mahler's framework for information fusion, the paper develops the optimal Bayes filter for this problem in the form of the… CONTINUE READING