Comparison of Unscented and Extended Kalman Filters with Application in Vehicle Navigation

Cheng Yang, Wenzhong Shi, Wu Chen

Research output: Journal article publicationJournal articleAcademic researchpeer-review

40 Citations (Scopus)


The Unscented Kalman Filter (UKF) is a well-known nonlinear state estimation method. It shows superior performance at nonlinear estimation compared to the Extended Kalman Filter (EKF). This paper is devoted to an investigation between UKF and EKF with different feedback control modes in vehicle navigation. Theoretical formulation, simulation and field tests have been carried out to compare the performance of UKF and EKF. The simulation and test results demonstrate that the estimated state of a UKF relies on the measurements and is less sensitive to historical model information. The results also indicate that UKF has benefits for prototype model design due to avoidance of calculation of a Jacobian matrix. EKF, however, is more computationally efficient and more stable.
Original languageEnglish
Pages (from-to)411-431
Number of pages21
JournalJournal of Navigation
Issue number2
Publication statusPublished - 1 Mar 2017


  • Kalman Filtering
  • Land vehicle Navigation
  • Nonlinear Filtering
  • Unscented Kalman Filter

ASJC Scopus subject areas

  • Oceanography
  • Ocean Engineering


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