… -level treatment of optimal smoothing methods based on Kalman filtering models, including …
approximation methods used for nonlinear applications, including “extended” Kalman filters …

… observation is the basic problem in using Kalman Filter in nonlinear systems, and introduced
UKF that is called Unscented Kalman Filter. This algorithm has two advantages than EKF. It …

… a working familiarity with Kalman filtering – both the theoretical and … It discusses a method
for assessing the magnitude of … methods that have been used in Kalman filtering with relative …

… To apply the methodology of the Kalman filter, it is necessary to assume the existence of an
approximating orbit (as Gauss did) or, in the parlance of the day, a reference trajectory. This …

… based on the Kalman filtering method has been tested. The … jobs (1) and (2), the Kalman
filtering still can dojob (3): Of course… Our practice has shown that the Kalman filtering method is a …

… (recursive) solution of the least-squares method. The … discrete Kalman filter, and the extended
Kalman filter. To help in developing a better feel for the operation and capability of the filter…

… Sandy Mahfouz proposed a method that combines machine learning with Kalman filter to
estimate instantaneous positions of a moving target. The application of his method can obtain …

… Chapter 7 investigates the use of the unscented Kalman filter as a potentially superior
alternative to the EKF [26–29]. Another interpretation of Kalman filtering is that of an optimization …

… This review aims to provide an accessible introduction to the methodology of invariant Kalman
filtering and to allow readers to gain insight into the relevance of the method as well as its …

… `filtering' task. We propose a special sequential Monte Carlo method, the mixture Kalman filter,
… Compared with a few available filtering methods including Monte Carlo methods, the gain …