Understanding Nonlinear Kalman Filters, Part I: Selection between EKF and UKF

نویسندگان

  • Matthew Rhudy
  • Yu Gu
چکیده

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. Part II presents detailed information about the implementation of EKF and UKF, including equations, tips, and example codes. Part III examines different techniques for determining the assumed noise characteristics of the system as well as tuning procedures for these nonlinear Kalman filters.

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تاریخ انتشار 2013