PulseExploreJournal ClubResearchersJournals
Instagram
HomeJournal ClubExplore
Synapse
⌘+K
Synapse
March 25, 2026TechnologiesOpen Access

Total Variational Indoor Localization Algorithm for Signal Manifolds in the Energy Domain

View Full Paper
Ask AI
Bookmark
Share

Authors

YWYunliang WangNQNingning QinSSShunyuan Sun

Discussion

Loading...

Member takes

Overview

This algorithm demonstrates improved positioning accuracy in indoor environments, suggesting effective navigation in complex layouts.

Key Points

  • The aim is to develop an indoor positioning algorithm that addresses signal feature distribution issues in non-line-of-sight environments.
  • Proposed EFM-GTV algorithm to address topological mismatches in signal and physical space.
  • Implemented UMAP manifold topology graph construction using fuzzy simplicial sets.
  • Developed a pruning strategy based on Jaccard similarity to eliminate false connections.
  • Reformulated positioning as a graph signal recovery task optimized through total variation techniques.
  • Achieved average positioning accuracy of 1.4267 m on real-world datasets.
  • Reduced maximum positioning error by over 50% compared to traditional weighted algorithms.
  • Successfully corrected NLOS errors leveraging manifold structure constraints.

Cite This Study

Wang et al. (2026) studied this question.

synapsesocial.com/papers/69c37bc2b34aaaeb1a67e800https://doi.org/10.3390/technologies14030191
View Full Paper
Ask AI
Bookmark
Share