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An Angle Recognition Algorithm for Tracking Moving Targets Using WiFi Signals with Adaptive Spatiotemporal

Liping Tian1, Liangqin Chen1, Zhimeng Xu1

  • 1School of Physics and Information Engineering, Fuzhou University, Fuzhou 350008, China.

Sensors (Basel, Switzerland)
|January 11, 2022
PubMed
Summary

This study introduces a novel WiFi-based angle estimation algorithm for tracking indoor moving targets. The new method achieves lower average angle errors compared to existing systems like Widar2.0 in various environments.

Keywords:
AOADBscanWiFiangle estimationchannel state information (CSI)least-squares method

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Area of Science:

  • Wireless communication
  • Indoor positioning systems
  • Signal processing

Background:

  • Accurate indoor tracking of moving targets is crucial for applications like robotics and surveillance.
  • Existing methods often struggle with multipath effects and require complex hardware.
  • WiFi-based solutions offer a cost-effective and ubiquitous alternative for indoor localization.

Purpose of the Study:

  • To propose a novel angle estimation algorithm for precise indoor target tracking using WiFi signals.
  • To improve the accuracy of angle of arrival (AOA) and time of flight (TOF) estimation in challenging indoor environments.
  • To mitigate the impact of multipath propagation on tracking performance.

Main Methods:

  • Phase calibration and static path elimination of channel state information (CSI) signals.
  • Joint estimation of angle of arrival (AOA) and time of flight (TOF).
  • DBscan spatiotemporal clustering for multipath effect mitigation.
  • Interpolation for time-continuous AOA extraction.
  • Least-squares method for final angle determination.

Main Results:

  • The proposed algorithm demonstrates reduced average angle estimation errors compared to Widar2.0.
  • Achieved average errors of 7.18° in classrooms, 3.62° in corridors, and 12.16° in offices.
  • Effective mitigation of multipath effects leading to improved tracking accuracy.

Conclusions:

  • The developed WiFi-based angle estimation algorithm provides a more accurate solution for indoor moving target tracking.
  • The algorithm's performance surpasses existing systems, particularly in complex indoor settings.
  • This approach offers a promising direction for enhancing indoor positioning technologies.