A Systematization of the Unscented Kalman Filter Theory

@article{Menegaz2015ASO,
  title={A Systematization of the Unscented Kalman Filter Theory},
  author={H. M. Menegaz and J. Ishihara and G. Borges and A. N. Vargas},
  journal={IEEE Transactions on Automatic Control},
  year={2015},
  volume={60},
  pages={2583-2598}
}
  • H. M. Menegaz, J. Ishihara, +1 author A. N. Vargas
  • Published 2015
  • Mathematics, Computer Science
  • IEEE Transactions on Automatic Control
  • In this paper, we propose a systematization of the (discrete-time) Unscented Kalman Filter (UKF) theory. We gather all available UKF variants in the literature, present corrections to theoretical inconsistencies, and provide a tool for the construction of new UKF's in a consistent way. This systematization is done, mainly, by revisiting the concepts of Sigma-Representation, Unscented Transformation (UT), Scaled Unscented Transformation (SUT), UKF, and Square-Root Unscented Kalman Filter (SRUKF… CONTINUE READING

    Tables and Topics from this paper.

    Unscented Kalman Filters for Riemannian State-Space Systems
    • 8
    • PDF
    A filtering approach based on MMAE for a SINS / CNS integrated navigation system
    • 3

    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 76 REFERENCES
    The unscented Kalman filter for nonlinear estimation
    • 3,068
    • Highly Influential
    • PDF
    Some Relations Between Extended and Unscented Kalman Filters
    • 233
    • Highly Influential
    • PDF
    Unscented Kalman filtering for additive noise case: augmented versus nonaugmented
    • 104
    On nonlinear transformations of stochastic variables and its application to nonlinear filtering
    • 25
    • PDF
    Aspects and comparison of matrix decompositions in unscented Kalman filter
    • 18
    • PDF
    On Unscented Kalman Filtering for State Estimation of Continuous-Time Nonlinear Systems
    • 177
    • PDF
    Cubature Kalman Filtering for Continuous-Discrete Systems: Theory and Simulations
    • 335
    • PDF
    New extension of the Kalman filter to nonlinear systems
    • 3,218
    • PDF