UUV cluster navigation data extraction fusion positioning algorithm with information geometry

Lingling Zhang, Shijiao Wu, Chengkai Tang

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

With the rapid development of the ocean economy, underwater unmanned vehicle (UUV) clusters have become the main tool for ocean development, but the complex interference and occlusion in the underwater environment have posed great challenges to the positioning of UUV clusters, becoming a key problem in the application of UUV clusters. To address this issue, this paper proposes a distributed heterogeneous navigation information geometric fusion positioning method for underwater unmanned vehicle clusters based on data extraction(DEFP-IG). This method converts the distributed navigation source information of UUVs into an information geometric probability model, and constructs a factor graph fusion architecture based on data extraction to improve the suppression of interference, thereby achieving high-precision positioning of UUV clusters. Comparing the method proposed in this paper with existing methods in different scenarios, the results show that the proposed method has higher positioning accuracy and good suppression capability for abrupt errors.

Original languageEnglish
Article number119646
JournalOcean Engineering
Volume314
DOIs
StatePublished - 15 Dec 2024

Keywords

  • Data extraction
  • Fusion positioning
  • Information geometry
  • Underwater unmanned vehicle clusters

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