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Indoor magnetic signature based localization algorithm without person-dependent parameter calibration.

Young Soo Suh1, Baatardorj Amarbayasgalan2

  • 1Department of Electrical Engineering, University of Ulsan, Namgu 680-749, Ulsan, Korea. yssuh@ulsan.ac.kr.

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Summary
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This study introduces an adaptive algorithm for indoor location estimation using magnetic fields and inertial sensors. It accurately estimates location and person-specific parameters without prior calibration, enhancing navigation systems.

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Area of Science:

  • Indoor positioning systems
  • Sensor fusion
  • Geophysics

Background:

  • Ambient magnetic fields inside buildings exhibit unique spatial variations.
  • Inertial and magnetic sensors can be utilized for indoor localization.
  • Pedestrian dead reckoning (PDR) methods often require manual calibration for personal parameters.

Purpose of the Study:

  • To develop an adaptive algorithm for accurate indoor location estimation.
  • To eliminate the need for person-specific parameter calibration in magnetic-based localization.
  • To integrate walking distance estimation with magnetic signature matching.

Main Methods:

  • An inertial/magnetic sensor was attached to the belt for data collection.
  • Walking distance was estimated using the linear relationship between step length and maximum acceleration.
  • An adaptive algorithm estimated location and person-dependent parameters (step length, hard iron) simultaneously.
  • Collected magnetic field data was compared against a pre-existing magnetic signature.

Main Results:

  • The proposed adaptive algorithm accurately estimated both location and person-dependent parameters.
  • Experiments demonstrated the effectiveness of the method in real-world indoor environments.
  • Simultaneous estimation of parameters removed the necessity for manual calibration steps.

Conclusions:

  • The adaptive algorithm offers a robust solution for indoor localization using magnetic field data.
  • This approach significantly simplifies the deployment and use of magnetic-based indoor positioning systems.
  • Accurate and automatic estimation of user-specific parameters is achievable, improving navigation accuracy.