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A Low-Cost and Efficient Indoor Fusion Localization Method.

Suqing Yan1,2, Chunping Wu2, Honggao Deng1

  • 1Guangxi Key Laboratory of Precision Navigation Technology and Application, Guilin University of Electronic Technology, Guilin 541004, China.

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Summary
This summary is machine-generated.

This study introduces a new indoor localization method fusing inertial sensors and acoustic signals for precise pedestrian tracking. It overcomes challenges of complex environments and sensor errors, improving accuracy and reliability.

Keywords:
acoustic signalimproved pedestrian dead reckonindoor localizationstep length estimation

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Area of Science:

  • Indoor positioning systems
  • Sensor fusion
  • Acoustic signal processing

Background:

  • Accurate indoor location is crucial for applications like navigation and heatmapping.
  • Ultrasonic methods offer temporal correlation but struggle with complex indoor environments.
  • Non-uniform facilities and signal interference pose significant challenges to existing localization techniques.

Purpose of the Study:

  • To develop a robust indoor localization method integrating inertial sensors and acoustic signals.
  • To enhance pedestrian dead reckoning (PDR) and time difference of arrival (TDOA) estimations.
  • To address outliers in acoustic localization and cumulative errors in inertial sensors.

Main Methods:

  • A fusion localization method combining inertial sensor data and acoustic signals.
  • Adaptive distance weighting for fusing TDOA and improved PDR estimations.
  • A threshold scheme to effectively eliminate outliers during the positioning process.

Main Results:

  • The proposed fusion method significantly improves localization accuracy compared to state-of-the-art techniques.
  • Successfully mitigates outliers common in indoor acoustic signal localization.
  • Effectively resolves cumulative error issues inherent in inertial sensor-based PDR.

Conclusions:

  • The integrated approach offers superior indoor localization performance in complex environments.
  • Provides a better trade-off between localization accuracy and system cost.
  • Demonstrates a viable solution for reliable and accurate pedestrian tracking indoors.