An optimization self-calibration method of rotational inertial navigation system based on genetic algorithm

Qian Ren, Bo Wang, Zhihong Deng, Mengyin Fu

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

1 Citation (Scopus)

Abstract

Navigation error of rotational inertial navigation system still diverges because of IMU errors. An improved self-calibration method is proposed to solve this problem. Least squares is utilized in identification of the error parameters with taking velocity errors as observations. The Genetic Algorithm(GA) is utilized to optimize the rotation angles, covariance matrix of the least squares is taken as fitness function of the GA. Simulation results show that compared to traditional method, the proposed method can improve the position accuracy significantly.

Original languageEnglish
Title of host publicationProceedings - 2013 International Conference on Mechatronic Sciences, Electric Engineering and Computer, MEC 2013
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2764-2767
Number of pages4
ISBN (Electronic)9781479925650
DOIs
Publication statusPublished - 2013
Event2013 International Conference on Mechatronic Sciences, Electric Engineering and Computer, MEC 2013 - Shenyang, China
Duration: 20 Dec 201322 Dec 2013

Publication series

NameProceedings - 2013 International Conference on Mechatronic Sciences, Electric Engineering and Computer, MEC 2013

Conference

Conference2013 International Conference on Mechatronic Sciences, Electric Engineering and Computer, MEC 2013
Country/TerritoryChina
CityShenyang
Period20/12/1322/12/13

Keywords

  • Genetic algorithm
  • Least square
  • Rotational inertial navigation system
  • Self-calibration

Fingerprint

Dive into the research topics of 'An optimization self-calibration method of rotational inertial navigation system based on genetic algorithm'. Together they form a unique fingerprint.

Cite this