The unscented Kalman filter for nonlinear estimation

@article{Wan2000TheUK,
  title={The unscented Kalman filter for nonlinear estimation},
  author={Eric 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. Wan, R. Van Der Merwe
  • Published 1 October 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… 

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