An adaptive UKF algorithm and its application for vehicle integrated navigation system

Xiao Yan Wu*, Chun Lei Song, Jia Bin Chen, Yong Qiang Han

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

In order to overcome the problems existing in Kalman filter(KF), extended Kalman filter(EKF) and unscented Kalman filter(UKF) in the vehicle integrated navigation system, a method is adopted to solve this problem. UKF algorithm is introduced, and an improved UKF was presented which is an adapted factor is introduced in UKF. It is shown, in vehicle integrated navigation system, UKF is superior to the EKF, AUKF is better than UKF, AUKF has better in reducing sensitivity of the process and the initial value of the statistical characteristics of the noise and the accuracy, reliability of the navigation solution.

Original languageEnglish
Title of host publicationProceedings of the 33rd Chinese Control Conference, CCC 2014
EditorsShengyuan Xu, Qianchuan Zhao
PublisherIEEE Computer Society
Pages787-791
Number of pages5
ISBN (Electronic)9789881563842
DOIs
Publication statusPublished - 11 Sept 2014
EventProceedings of the 33rd Chinese Control Conference, CCC 2014 - Nanjing, China
Duration: 28 Jul 201430 Jul 2014

Publication series

NameProceedings of the 33rd Chinese Control Conference, CCC 2014
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

ConferenceProceedings of the 33rd Chinese Control Conference, CCC 2014
Country/TerritoryChina
CityNanjing
Period28/07/1430/07/14

Keywords

  • adapted factor
  • extended Kalman filter
  • unscented Kalman filter
  • vehicle navigation

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