A strong tracking cubature kalman filter for nonlinear estimation

Yong Qi Wang, Feng Yang, Yan Liang, Quan Pan

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

1 Scopus citations

Abstract

In this paper, a novel method based on cubature Kalman filter (CKF) and strong tracking filter (STF) has been proposed for nonlinear state estimation problem. The proposed method is named as strong tracking cubature Kalman filter (STCKF). In the STCKF, a scaling factor derived from STF is added and it can be tuned online to adjust the filtering gain accordingly. Simulation results indicate STCKF outperforms over EKF and CKF in state estimation accuracy.

Original languageEnglish
Title of host publicationMachinery Electronics and Control Engineering II
Pages1115-1119
Number of pages5
DOIs
StatePublished - 2013
Event2012 2nd International Conference on Machinery Electronics and Control Engineering, ICMECE 2012 - Jinan, Shandong, China
Duration: 29 Dec 201230 Dec 2012

Publication series

NameApplied Mechanics and Materials
Volume313-314
ISSN (Print)1660-9336
ISSN (Electronic)1662-7482

Conference

Conference2012 2nd International Conference on Machinery Electronics and Control Engineering, ICMECE 2012
Country/TerritoryChina
CityJinan, Shandong
Period29/12/1230/12/12

Keywords

  • CKF
  • EKF
  • Nonlinear estimation
  • STF

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