Observable degree analysis of DGPS/SINS calibration based on singular value decomposition

Mingjie Wang, Jiabin Chen, Chunlei Song, Yongqiang Han, Chong Qin

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

4 Citations (Scopus)

Abstract

The observable degree of linear time-varying system is often analyzed after Kalman filter is designed, and it's the key parameter to examine the accuracy and rate of convergence of the Kalman filter. However, traditional approaches of observable degree analysis cannot simultaneously meet the requirements in engineering applications. This necessitates the development of observable degree analysis. This paper is on the basis that inertial components error model has been set, and an approach of multiposition for calibration is introduced, which aims at improving the accuracy of calibration of strapdown inertial navigation system (SINS) based on differential global positioning system (DGPS). During the process, first, definitions of observable degree that researchers have proposed are introduced. Then, an approach of observable analysis, which can transform linear time-varying system to piece-wise constant system (PWCS), is disserted. And next, singular value decomposition (SVD) is applied to observable matrix based on PWCS, which is used to analyze whether the observability has been improved through observing the changes of singular values. Finally, results of simulation demonstrate that observable degree has been well improved, and observable parameter can predict Kalman filtering errors of system states precisely.

Original languageEnglish
Title of host publicationProceedings of the 35th Chinese Control Conference, CCC 2016
EditorsJie Chen, Qianchuan Zhao, Jie Chen
PublisherIEEE Computer Society
Pages5648-5653
Number of pages6
ISBN (Electronic)9789881563910
DOIs
Publication statusPublished - 26 Aug 2016
Event35th Chinese Control Conference, CCC 2016 - Chengdu, China
Duration: 27 Jul 201629 Jul 2016

Publication series

NameChinese Control Conference, CCC
Volume2016-August
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference35th Chinese Control Conference, CCC 2016
Country/TerritoryChina
CityChengdu
Period27/07/1629/07/16

Keywords

  • Kalman filter
  • PWCS
  • SVD
  • calibration
  • observable degree

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