Iteration and SUT-based variational filter

An iterative method based on the concept of variational optimality and Ensemble Transform (ET) as well as Scaled Unscented Transform (SUT), called Iteration and SUT-based Variational Filter (ISVF), is introduced for nonlinear and high dimensionality dynamics. Using the SUT Kalman filter (SUKF) [1], the ISVF suggests a novel correction scheme for estimation of ensemble mean and corresponding ensemble covariance, which incorporates a variational minimization as well as a ET-like covariance update into the ordinary correction. Moreover for dealing with the dynamics with high dimensionality, the Truncated Singular Value Decomposition (TSVD) is applied to generate a size-reduced set of sigma points. Finally numerical experiments are performed on Lorenz-95 model for efficiency validating.