Corpus ID: 204008630

Improving the Convergence of the Iterative Ensemble Kalman Filter by Resampling

@article{Wu2019ImprovingTC,
  title={Improving the Convergence of the Iterative Ensemble Kalman Filter by Resampling},
  author={Jiacheng Wu and J. Wang and S. Shadden},
  journal={arXiv: Optimization and Control},
  year={2019}
}
The iterative ensemble Kalman filter (IEnKF) is widely used in inverse problems to estimate system parameters from limited observations. However, the IEnKF, when applied to nonlinear systems, can be plagued by poor convergence. Here we provide a comprehensive convergence analysis of the IEnKF and propose a new method to improve its convergence. A theoretical analysis of the standard IEnKF is presented and we demonstrate that the interaction between the nonlinearity of the forward model and the… Expand
2 Citations

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