Controlled interacting particle systems such as the ensemble Kalman filter (EnKF) and feedback (FPF) are numerical algorithms to approximate solution of nonlinear filtering problem in continuous time. The distinguishing feature these is that Bayesian update step implemented using a control law. It has been noted literature law not unique. This main addressed this article. To obtain unique law, ...

As one of the most adopted sequential data assimilation methods in many areas, especially those involving complex nonlinear dynamics, the ensemble Kalman filter (EnKF) has been under extensive investigation regarding its properties and efficiency. Compared to other variants of the Kalman filter (KF), EnKF is straightforward to implement, as it employs random ensembles to represent solution stat...

Recently various versions of ensemble Kalman filters (EnKF) has been proposed and studied. This work concerns, in a mathematically rigorous manner, the relative performance of two major versions of EnKF when the forecast ensemble is non-Gaussian. The approach is based on the stability of the filtering methods against small model violations, using the expected squared L2 distance as a measure of...