Neural network-aided adaptive UKF for integrated underwater navigation

Meng Wu, Ying Weng

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

Abstract

Gravity aided navigation and geomagnetism aided navigation are equally important methods in the field of underwater navigation. However, the former is affected by terrain fluctuations, and the latter is sensitive to time-varying noise. Considering the characteristics that the gravity gradient vector can avoid the influence of time-varying noise and is less sensitive to terrain fluctuations, we propose to integrate the gravity gradient vector and geomagnetic vector together to achieve the merits of each aided navigation method. The gravity gradient vector and geomagnetic vector are used as measurement information from both local neural network-aided adaptive UKF filters, and then an information fusion algorithm based on weighted least squares estimation is used to combine the estimated values from each local filter to form an optimal estimated state value. Finally, the optimal estimated value is used to update the output values from each local neural network –aided adaptive UKF filter. Experimental results prove the feasibility of this integrated navigation method.

Original languageEnglish
Title of host publicationNeural Information Processing - 22nd International Conference, ICONIP 2015, Proceedings
EditorsWeng Kin Lai, Qingshan Liu, Tingwen Huang, Sabri Arik
PublisherSpringer Verlag
Pages301-310
Number of pages10
ISBN (Print)9783319265346
DOIs
Publication statusPublished - 2015
Externally publishedYes
Event22nd International Conference on Neural Information Processing, ICONIP 2015 - Istanbul, Turkey
Duration: 9 Nov 201512 Nov 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9490
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference22nd International Conference on Neural Information Processing, ICONIP 2015
Country/TerritoryTurkey
CityIstanbul
Period9/11/1512/11/15

Keywords

  • Adaptive UKF
  • Geomagnetic vector
  • Gravity gradient vector
  • Information fusion
  • Neural network
  • Underwater navigation
  • Weighted least square estimation

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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