Kalman filters provide an important technique for estimating the states of engineering systems. With several variations of nonlinear Kalman filters, there is a lack of guidelines for filter selection with respect to a specific research or engineering application. This creates a need for an in-depth discussion of the intricacies of different nonlinear Kalman filters. Particularly of interest for practical state estimation applications are the Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF). This tutorial is divided into three self-contained articles. Part I gives a general comparison of EKF and UKF, and offers a guide to the selection of a filter.
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Hi,
ReplyDeletePlease, I want a code that implements DUAL UKF.
1. Both the state-transition model and observation,measurement model are nonlinear and have parameters to be estimated.
Hi Mr Gu,
ReplyDeleteI tried searching for third part of Understanding Nonlinear Kalaman Filters, and was unsuccessful in finding one. I would be extremely grateful if you could point me to the third part of the article. Thanking you in advance