UUV cluster navigation data extraction fusion positioning algorithm with information geometry

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. • We establish information geometry probabilistic model. • We propose a distributed heterogeneous navigation fusion positioning method. • Our positioning accuracy is higher. • Our positioning stability is higher.