Underwater Unmanned Vehicle Clusters Cooperative Positioning Method

Shijiao Wu, Lingling Zhang, Chengkai Tang, Yimeng Gao

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

Abstract

Nowadays, UUV clusters have become the main carriers for ocean environment monitoring. In this application, the positioning of UUV nodes during voyages is of great importance. A cooperative positioning method for UUV clusters is presented in this paper. It utilizes factor graphs to fuse ranging information from each UUV node, and predicts movement path based on multiple confocal positioning models. The comparison results demonstrate that the proposed method achieves higher positioning accuracy, faster convergence speed, and good suppression capability for mutation errors.

Original languageEnglish
Title of host publication2024 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350366556
DOIs
StatePublished - 2024
Externally publishedYes
Event14th IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2024 - Hybrid, Bali, Indonesia
Duration: 19 Aug 202422 Aug 2024

Publication series

Name2024 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2024

Conference

Conference14th IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2024
Country/TerritoryIndonesia
CityHybrid, Bali
Period19/08/2422/08/24

Keywords

  • Cooperative positioning
  • Factor Graph
  • Information confidence models
  • Underwater unmanned vehicle clusters

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