The unscented Kalman filter for nonlinear estimation

@article{Wan2000TheUK,
  title={The unscented Kalman filter for nonlinear estimation},
  author={E. A. Wan and R. van der Merwe},
  journal={Proceedings of the IEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium (Cat. No.00EX373)},
  year={2000},
  pages={153-158}
}
  • E.A. Wan, R. van der Merwe
  • Published 2000
  • Mathematics
  • Proceedings of the IEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium (Cat. No.00EX373)
  • This paper points out the flaws in using the extended Kalman filter (EKE) and introduces an improvement, the unscented Kalman filter (UKF), proposed by Julier and Uhlman (1997). A central and vital operation performed in the Kalman filter is the propagation of a Gaussian random variable (GRV) through the system dynamics. In the EKF the state distribution is approximated by a GRV, which is then propagated analytically through the first-order linearization of the nonlinear system. This can… CONTINUE READING

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