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Classical algorithms of sound source localization with beamforming, TDOA and high-resolution spectral estimation.

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Sound Source Localization

Classical algorithms of sound source localization with beamforming, TDOA and high-resolution spectral estimation.

Usage

matlab -nodesktop -nosplash –r matlabfile (name of .m)

Algorithm Interpretation

  • Beamforming: a spatial filtering method, is a signal processing technique used in sensor arrays for directional signal transmission or reception.
  • MUSIC: Multiple Signal Classification
  • ESPRIT: Estimation of Signal Parameters via Rotational Invariance Technique
  • MVDR: Minimum Variance Distortionless Response
  • GCC-PHAT: Generalized Cross Correlation - Phase Transform (TDOA estimation)
  • SRP-PHAT: Steered Response Power - Phase Transform

Reference Paper

  • Paper 1
    • Title: Comparison of Direction of Arrival (DOA) Estimation Techniques for Closely Spaced Targets
    • Authors: Nauman Anwar Baig and Mohammad Bilal Malik
    • Published: International journal of future computer and communication 2, no. 6 (2013): 654
  • Paper 2

Results

1. Algorithm Summary

1.1 Classical Beamforming

1.2 Min-Norm

1.3 MUSIC

1.4 MVDR

2. Beamforming

2.1 microphone array

2.2 Two-dimensional map of localization result

2.3 Three-dimensional map of localization result

3. MUSIC

3.1 matlab_implement2 (BEST)

3.3 matlab_implement1

Reference Book

Reference Website

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  • Jupyter Notebook 78.7%
  • MATLAB 17.0%
  • Python 4.3%