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Research on a Sound Source Localization Method for UAV Detection Based on Improved Empirical Mode Decomposition.

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This study presents a novel acoustic localization method for unmanned aerial vehicles (UAVs) using improved Empirical Mode Decomposition (EMD) and an adaptive frequency window. The technique achieves high accuracy for real-time UAV detection and tracking.

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Area of Science:

  • Acoustics and Signal Processing
  • Aerospace Engineering
  • Robotics and Control Systems

Background:

  • Traditional radar and visual tracking methods for unmanned aerial vehicles (UAVs) face limitations in certain operational environments.
  • Accurate localization is crucial for UAV traffic management, security, and operational safety.
  • Developing alternative localization techniques is essential for expanding UAV operational capabilities.

Purpose of the Study:

  • To propose and validate an innovative acoustic source localization method for UAVs.
  • To enhance the accuracy and reliability of UAV localization, particularly when radar or visual methods are infeasible.
  • To provide an efficient and real-time solution for detecting and locating small UAVs.

Main Methods:

  • Applied smoothing filtering and Robust Empirical Mode Decomposition (REMD) to UAV flight signals.
  • Utilized an adaptive frequency window, optimized by Grey Wolf Optimizer (GWO), to extract relevant Intrinsic Mode Function (IMF) components.
  • Employed the Chan-Taylor localization algorithm with weighted least squares, using calculated sensor time differences for target positioning.

Main Results:

  • The proposed acoustic localization method demonstrated robustness and high performance in simulations and real-world tests.
  • Localization errors were consistently below 5% within a 15 m × 15 m measurement area.
  • The method proved effective for real-time detection and location determination of small UAVs.

Conclusions:

  • The developed acoustic localization technique offers an efficient and accurate solution for UAV detection.
  • The integration of REMD, adaptive frequency windows, and advanced localization algorithms enhances localization precision.
  • This method provides a viable alternative for UAV localization in challenging environments where conventional methods fail.