Fault detection in SINS/CNS/GPS integrated system based on federated filter

Hua Zong*, Bo Wang, Zhun Liu, Lei Gao, Xiao Qin Ji, Sun Li

*Corresponding author for this work

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

3 Citations (Scopus)

Abstract

In order to improve the reliability and accuracy of the SINS/CNS/GPS integrated system, a fault-tolerant integrated navigation algorithm based on federated Kalman filter is proposed. The architecture of the federated Kalman filter includes a master filter, two local filters, and two fault detection functions which are based on the residuals of the local filter. Because the choosing of threshold for fault detection is very important to fault-tolerant integrated navigation system, a new method of Dual-threshold detection is built and used in fault detection. The simulation results show that the proposed algorithm using Dual-threshold detection based on federated Kalman filter is effective, and the reliability and accuracy of the integrated navigation system are improved.

Original languageEnglish
Title of host publicationProceedings of the 33rd Chinese Control Conference, CCC 2014
EditorsShengyuan Xu, Qianchuan Zhao
PublisherIEEE Computer Society
Pages608-612
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

  • Dual-threshold detection
  • Fault detection
  • Federated Kalman filter

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