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Real-time TDOA-based stationary sound source direction finding

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Abstract

Performance improvement of sound source direction finding is a critical acoustic task in target localization, tracking, and navigation as an NP problem that suffers from sound reflection and noise in passive or active methods. The accuracy of prediction increases by integrating more information about the signal specification, source position, sensor attributes, microphone array topology, characteristics of hardware architecture, dimension of distance, the status of environmental sounds, climatic conditions, effects of signal propagation, properties of barriers, and setting of initial estimation which is time-consuming. This paper presents a scalable method of sound source direction finding based on the time-difference-of-arrival approach to improve the accuracy of predictions of three-dimensional space in an outdoor environment. The real-time passive process is robust to sound reflection and ambient noise that decreases the running-time and increases the accuracy significantly through complexity reduction by proposing a novel Krill Herd algorithm based on successive unconstrained minimization technique. Experimental results of different actual and simulated datasets show the angle error amounts of Azimuth and Elevation are 0.7164∘ and 1.5054∘ in the near-field, and are 1.0260∘ and 0.2071∘ in the far-field, respectively. Performance evaluation of the passive proposed process shows that higher accuracy can be reached by using more parallel distributed sensor arrays.

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Authors and Affiliations

  1. Computer Engineering Department, Shahed University, Tehran, Iran

    Zahra Heydari & Aminollah Mahabadi

  2. Acoustic Research Center, Shahed University, Tehran, Iran

    Zahra Heydari & Aminollah Mahabadi

  3. School of Computer Science, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran

    Aminollah Mahabadi

Authors
  1. Zahra Heydari
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  2. Aminollah Mahabadi
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Correspondence to Aminollah Mahabadi.

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This Article has been written by the stated authors, is original and has not been previously published. They have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Heydari, Z., Mahabadi, A. Real-time TDOA-based stationary sound source direction finding. Multimed Tools Appl 82, 39929–39960 (2023). https://doi.org/10.1007/s11042-023-14741-2

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  • DOI: https://doi.org/10.1007/s11042-023-14741-2

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