Increasing the convergence rate of theextended kalman filter

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations


Efforts to improve the convergence of the Extended Kalman Filter (EKF) are presented. Three different scaling parameters are introduced which change the convergence properties of the estimation. Using an example nonlinear filtering problem, these scaling parameters are shown to increase the convergence rate of the EKF but at the cost of increased persistent estimation error. To remedy this, a time-varying scaling parameter is developed, which maintains the increased convergence rate of the filter without degrading the persistent estimation performance of the filter.

Original languageEnglish (US)
Title of host publicationAIAA Infotech at Aerospace
PublisherAmerican Institute of Aeronautics and Astronautics Inc.
ISBN (Electronic)9781624103384
StatePublished - Jan 1 2015
EventAIAA Infotech @ Aerospace 2015 - Kissimmee, United States
Duration: Jan 5 2015Jan 9 2015

Publication series

NameAIAA Infotech at Aerospace


OtherAIAA Infotech @ Aerospace 2015
Country/TerritoryUnited States

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering


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