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April 7, 2026SensorsOpen Access

Seamless Indoor and Outdoor Navigation Using IMU-GNSS Sensor Data Fusion

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Authors

BABismark Kweku Asiedu AsanteHIHiroki Imamura

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Overview

This framework improves localization accuracy in wearable systems, enhancing navigation for the visually impaired.

Key Points

  • The research aims to develop a robust system for navigating both indoor and outdoor environments using sensor data fusion.
  • Developed a GNSS-IMU sensor fusion framework using a Physics-Informed Neural Network (PINN) and Extended Kalman Filter (EKF)
  • Employed GNSS for outdoor localization and PINN-enhanced IMU-based dead reckoning indoors
  • Implemented the system on a compact, energy-efficient wearable platform
  • Evaluated using real-world pedestrian trajectories in various environments
  • Improved localization accuracy across indoor and outdoor settings
  • Significantly reduced drift during indoor navigation
  • Stable transitions between indoor and outdoor navigation zones
  • Outperformed conventional GNSS-IMU fusion methods

Cite This Study

Asante et al. (2026) studied this question.

synapsesocial.com/papers/69d49f8ab33cc4c35a227f9chttps://doi.org/10.3390/s26072215
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