… the Kalman filter and the Extended Kalman filter dynamics. The general filtering problem is
… This section presents basic results on the estimation of a random parameter vector based …

… Our goal is to approximate the best unbiased estimate, in … Like in the standard Kalman
Filter we find out Kk by minimizing … The IEKF tries to linearize it about the most recent estimate, …

… as the joint extended Kalman filter. … state filter estimates the state using the current model
estimate ewk, while the EKF weight filter estimates the weights using the current state estimate …

… The Kalman filter (KF) is the optimal estimator that minimizes … Kalman filter implementations
called extended Kalman filters … and then designing the Kalman filter gain for the linearized …

… filtering is an important and wellstudied field of estimation … , among which perhaps the
extended Kalman filter (EKF) is the … and on the use of linear estimation theory (the Kalman filter). …

… estimator, which can be used for combined estimation of vehicle states and parameters. The
estimator is realised using the dual extended Kalman filter (… of two Kalman filters running in …

… Numerical robustness of extended Kalman filtering based state estimation in ill‐conditioned
continuous‐discrete nonlinear stochastic chemical systems. International Journal of Robust …

… to estimate lost motion vectors [3], [4]. For recursive nonlinear estimation problem is extended
Kalman filter … 4 for extended Kalman filter we can see that Kalman filter gives better results …

… of samples required to reconstruct a point estimate within a given relative error increases …
the estimation properties of both the extended Kalman filter and moving-horizon estimation …

… This paper applies the polynomial chaos theory to the problem of parameter estimation,
using direct stochastic collocation and an approach based on the Extended Kalman Filter (EKF). …