A new class of iterated linearization-based nonlinear filters, dubbed dynamically iterated
filters, is presented. Contrary to regular iterated filters such as the iterated extended Kalman …

Typical iterated filters, such as the iterated extended Kalman filter (IEKF), iterated unscented
Kalman filter (IUKF), and iterated posterior linearization filter (IPLF), have been developed to …

The two most popular solutions to the nonlinear filtering problem are the Extended Kalman
filter (EKF) and the Iterated Extended Kalman filter (IKF). Both are sub-optimal algorithms …

This letter presents the development of novel iterated filters and smoothers that only require
specification of the conditional moments of the dynamic and measurement models. This …

The unscented Kalman filter (UKF) is a very popular solution for estimation of the state in
nonlinear systems. Similar to the extended Kalman filter (EKF) and contrary to the Kalman …

Various methods have been proposed for the nonlinear filtering problem, including the
extended Kalman filter (EKF), iterated extended Kalman filter (IEKF), unscented Kalman filter …

Efforts to improve the convergence of the Extended Kalman Filter (EKF) are presented.
Three different scaling parameters are introduced which change the convergence properties …

This paper is concerned with discrete time Kalman-type filtering with state transition and
measurement noises that may be non-additive or non-linearly transformed. More …

Nonlinear measurement models pose a challenge to linear filters. The ensemble Kalman
filter (EnKF) is a popular choice despite its tendency to diverge in systems with highly …

This letter investigates relationships between iterated filtering algorithms based on statistical
linearization, such as the iterated unscented Kalman filter (iukf), and filtering algorithms …