Research on the compensation in MEMS gyroscope random drift based on time-series analysis and Kalman filtering

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

12 Citations (Scopus)

Abstract

From a practical point of view, the paper introduces an effective compensation method for MEMS gyroscope random drift. First, the MEMS data will be collected and pretreated by using time-series analysis so as to get the random drift signals. Then the ARMA model will be established and the signals will be filtered by Kalman filtering. The compensation results by Kalman filtering shows that the proposed method can effectively reduce random drift not only on the conditions but also at constant rates.

Original languageEnglish
Title of host publicationProceedings of the 34th Chinese Control Conference, CCC 2015
EditorsQianchuan Zhao, Shirong Liu
PublisherIEEE Computer Society
Pages2078-2082
Number of pages5
ISBN (Electronic)9789881563897
DOIs
Publication statusPublished - 11 Sept 2015
Event34th Chinese Control Conference, CCC 2015 - Hangzhou, China
Duration: 28 Jul 201530 Jul 2015

Publication series

NameChinese Control Conference, CCC
Volume2015-September
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference34th Chinese Control Conference, CCC 2015
Country/TerritoryChina
CityHangzhou
Period28/07/1530/07/15

Keywords

  • Kalman filtering
  • MEMS gyroscope
  • random drift
  • time series models

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