Unscented filtering and nonlinear estimation

@article{Julier2004UnscentedFA,
  title={Unscented filtering and nonlinear estimation},
  author={Simon J. Julier and Jeffrey K. Uhlmann},
  journal={Proceedings of the IEEE},
  year={2004},
  volume={92},
  pages={401-422}
}
The extended Kalman filter (EKF) is probably the most widely used estimation algorithm for nonlinear systems. However, more than 35 years of experience in the estimation community has shown that is difficult to implement, difficult to tune, and only reliable for systems that are almost linear on the time scale of the updates. Many of these difficulties arise from its use of linearization. To overcome this limitation, the unscented transformation (UT) was developed as a method to propagate mean… 

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