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Sina Hafezi1, Alastair H Moore1, Patrick A Naylor1

  • 1Department of Electrical and Electronic Engineering, Imperial College London, SW7 2AZ, United Kingdom.

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Summary

This study introduces new methods for direction-of-arrival (DOA) estimation, improving accuracy for multiple sources even when masked. The approach enhances detection and localization in challenging acoustic environments.

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Area of Science:

  • Acoustics and Signal Processing
  • Computational Auditory Scene Analysis

Background:

  • Conventional wideband multi-source (MS) direction-of-arrival (DOA) estimation relies on single-source (SS) assumptions in time-frequency (TF) bins, often using the W-disjoint orthogonality (WDO) property.
  • The WDO assumption is frequently violated in scenarios with multiple simultaneously active sources, leading to failures in detecting or accurately localizing masked sources.

Purpose of the Study:

  • To develop novel analytical approaches for multi-source DOA estimation that overcome the limitations of SS-based methods.
  • To improve the accuracy and robustness of DOA estimation in challenging acoustic environments with masked sources.

Main Methods:

  • Two analytical approaches for narrowband DOA estimation under the MS assumption in the spherical harmonic domain were proposed.
  • The first method utilizes eigenvalue decomposition to transform a MS scenario into multiple SS scenarios for individual estimation.
  • The second method analytically estimates two DOAs per bin, assuming the presence of two active sources.

Main Results:

  • The proposed methods demonstrate significant improvements in DOA estimation accuracy, doubling the performance compared to baseline methods.
  • Enhanced robustness to sensor noise was observed in the evaluated scenarios.
  • Successful detection and localization of masked sources were achieved, addressing limitations of conventional SS-based techniques.

Conclusions:

  • The developed analytical approaches offer a more robust and accurate solution for multi-source DOA estimation, particularly in complex acoustic scenes.
  • These methods effectively handle masked sources by relaxing the strict SS assumption, advancing the field of acoustic signal processing.