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Amplitude Modeling of Specular Multipath Components for Robust Indoor Localization.

Hong Anh Nguyen1, Van Khang Nguyen1, Klaus Witrisal2

  • 1School of Electronics and Telecommunications, Hanoi University of Science and Technology, Hanoi 11615, Vietnam.

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Summary

This study analyzes a Gaussian Process Regression (GPR) channel model for Ultra-Wide Bandwidth (UWB) and mm-wave systems. The model accurately predicts signal amplitudes and enhances positioning system robustness by improving environmental awareness.

Keywords:
UWB radiosenvironmental awarenessgaussian process regressiongeometry-based channel modelinglocation awarenessmm-wave radiosmultipath-assisted positioningsingle-anchor positioningsituational awareness

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Area of Science:

  • Wireless communication
  • Radio propagation modeling
  • Signal processing

Background:

  • Ultra-Wide Bandwidth (UWB) and mm-wave systems can resolve specular multipath components (SMCs).
  • Geometric models describe SMC delays and angles, but amplitude modeling requires data-driven approaches.
  • Gaussian Process Regression (GPR) offers a method for predicting SMC amplitudes.

Purpose of the Study:

  • To analyze the applicability of a GPR-based channel model for UWB and mm-wave systems.
  • To evaluate channel features like energy capture, resolvable SMCs, and ranging information.
  • To assess the model's potential for multipath-resolved, single-anchor positioning systems.

Main Methods:

  • Utilizing channel impulse response measurements to resolve SMCs.
  • Applying a GPR model to predict SMC amplitudes.
  • Analyzing channel features and evaluating positioning performance using predicted channel knowledge.

Main Results:

  • The GPR-based model demonstrates effective prediction of SMC amplitudes.
  • Analysis of energy capture, number of SMCs, and ranging information confirms model applicability.
  • The model enhances robustness against position estimation outliers in positioning systems.

Conclusions:

  • The multipath-resolved, GPR-based channel model is applicable for UWB and mm-wave systems.
  • The model provides valuable insights into propagation channel characteristics.
  • Environmental awareness from the model improves positioning system reliability.