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A Robust Adaptive Filtering Framework for Smartphone GNSS/PDR-Integrated Positioning.

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Summary
This summary is machine-generated.

This study introduces a new smartphone navigation method using a Robust Adaptive Cubature Kalman Filter (RACKF) to improve outdoor positioning accuracy. The RACKF enhances Global Navigation Satellite System (GNSS) and Pedestrian Dead Reckoning (PDR) fusion, offering reliable navigation in challenging urban environments.

Keywords:
complex environmentsmulti-sensor fusionpedestrian dead reckoningrobust adaptive filteringsmartphone positioning

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Area of Science:

  • Navigation Systems
  • Signal Processing
  • Geomatics Engineering

Background:

  • Outdoor pedestrian positioning via smartphones faces challenges in urban canyons due to degraded Global Navigation Satellite System (GNSS) signals and cumulative errors in Pedestrian Dead Reckoning (PDR).
  • Existing methods struggle with accuracy and reliability in environments with poor satellite visibility.

Purpose of the Study:

  • To develop a novel fusion method for accurate and continuous outdoor pedestrian positioning using smartphones.
  • To enhance the robustness and accuracy of navigation in challenging urban environments.

Main Methods:

  • A two-stage filtering architecture based on a Robust Adaptive Cubature Kalman Filter (RACKF) was proposed.
  • The first stage uses a quaternion-based RACKF for sensor fusion (gyroscope, magnetometer) for heading estimation.
  • The second stage fuses GNSS observations with an enhanced 3D PDR solution, incorporating adaptive noise estimation, outlier suppression (M-estimator), and differential barometric height.

Main Results:

  • The proposed method achieved a horizontal positioning accuracy of 3.28 m (RMSE).
  • It demonstrated superior performance compared to standalone GNSS.
  • Significant improvements were observed in 3D PDR accuracy, by 25.97% and 10.39% respectively.

Conclusions:

  • The novel RACKF-based fusion method provides a practical, infrastructure-free solution for robust smartphone-based outdoor navigation.
  • The adaptive noise estimation and outlier suppression mechanisms enhance positioning reliability in complex environments.
  • This approach effectively overcomes GNSS signal degradation and PDR cumulative errors.