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This study introduces a novel multi-person tracking system using a single Ultra-Wideband (UWB) radar. The method enhances human detection and reduces computational load, even with overlapping radar signals.

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Area of Science:

  • Radar Systems Engineering
  • Human Motion Analysis
  • Signal Processing

Background:

  • Multi-person tracking is crucial for surveillance and human-computer interaction.
  • Existing methods often require multiple sensors or complex algorithms.
  • Single-sensor tracking with limited antennas presents unique challenges in signal resolution and target separation.

Purpose of the Study:

  • To propose a multi-person tracking framework using a single Ultra-Wideband (UWB) radar with a minimal antenna array.
  • To enhance the detectability of multiple individuals and reduce computational complexity.
  • To address challenges in tracking through crossing or merging radar echoes.

Main Methods:

  • Utilizing a single UWB radar with an antenna array optimized for trilateration.
  • Implementing a simplified Time-of-Arrival (TOA) estimation and association method.
  • Developing a novel antenna height compensation technique.
  • Employing high-rate, fine-range resolution radar measurements with tuned processing parameters.

Main Results:

  • Successfully tracked multiple people moving in close proximity within an experimental scenario.
  • Demonstrated improved human detectability and reduced computational complexity through strategic antenna placement.
  • Achieved continuous tracking even when radar echoes crossed or merged.
  • Validated the effectiveness of the proposed TOA estimation, association, and height compensation methods.

Conclusions:

  • The proposed UWB radar tracking framework enables effective multi-person tracking with minimal hardware.
  • Strategic antenna placement and advanced signal processing significantly decrease localization error and increase tracking accuracy.
  • This approach offers a computationally efficient and accurate solution for human tracking applications.