Research and Realization of Sound Source Localization Algorithms Based on the Time Difference of Arrival

2015 ◽  
Vol 12 (16) ◽  
pp. 5995-6003 ◽  
Author(s):  
Shuying Yang
Keyword(s):  
Source Localization ◽  
Sound Source ◽  
Time Difference ◽  
Sound Source Localization ◽  
Time Difference Of Arrival ◽  
Localization Algorithms

scholarly journals A two-stage approach for passive sound source localization based on the SRP-PHAT algorithm

2020 ◽  
Vol 9 ◽  
Author(s):  
M.A. Awad-Alla ◽  
Ahmed Hamdy ◽  
Farid A. Tolbah ◽  
Moatasem A. Shahin ◽  
M.A. Abdelaziz
Keyword(s):  
Source Localization ◽  
Sound Source ◽  
Microphone Array ◽  
Search Space ◽  
Time Difference ◽  
Sound Source Localization ◽  
Time Difference Of Arrival ◽  
Error Coefficient ◽  
Viable Approach ◽  
Application Requirements

Abstract This paper presents a different approach to tackle the Sound Source Localization (SSL) problem apply on a compact microphone array that can be mounted on top of a small moving robot in an indoor environment. Sound source localization approaches can be categorized into the three main categories; Time Difference of Arrival (TDOA), high-resolution subspace-based methods, and steered beamformer-based methods. Each method has its limitations according to the search or application requirements. Steered beamformer-based method will be used in this paper because it has proven to be robust to ambient noise and reverberation to a certain extent. The most successful and used algorithm of this method is the SRP-PHAT algorithm. The main limitation of SRP-PHAT algorithm is the computational burden resulting from the search process, this limitation comes from searching among all possible candidate locations in the searching space for the location that maximizes a certain function. The aim of this paper is to develop a computationally viable approach to find the coordinate location of a sound source with acceptable accuracy. The proposed approach comprises two stages: the first stage contracts the search space by estimating the Direction of Arrival (DoA) vector from the time difference of arrival with an addition of reasonable error coefficient around the vector to make sure that the sound source locates inside the estimated region, the second stage is to apply the SRP-PHAT algorithm to search only in this contracted region for the source location. The AV16.3 corpus was used to evaluate the proposed approach, extensive experiments have been carried out to verify the reliability of the approach. The results showed that the proposed approach was successful in obtaining good results compared to the conventional SRP-PHAT algorithm.

scholarly journals A modified cross-correlation algorithm to achieve the time difference of arrival in sound source localization

2019 ◽  
Vol 52 (3-4) ◽  
pp. 212-221 ◽  
Author(s):  
Na Zhu ◽  
Tamim Reza
Keyword(s):  
Source Localization ◽  
Sound Source ◽  
Cross Correlation ◽  
Signal To Noise Ratio ◽  
Time Difference ◽  
Sound Source Localization ◽  
Time Data ◽  
Time Difference Of Arrival ◽  
Correlation Algorithm ◽  
Target Source

The accuracy in ranging and direction in locating a target source is crucial in sound source localization and different methods have been proposed due to important applications of sound source localization. One of the methods in sound source localization is triangulation with the time difference of arrival information. In this literature, a modified cross-correlation algorithm is introduced to increase the accuracy in time difference of arrival, thus further improving the sound source localization results. A numerical model is generated by assuming multiple sound sources broadcasting in room environment and the location of the target sound source is identified with the triangulation algorithm. Real-time data are produced through experimental setup using an array of four microphones with a target source and background noise. The signals are processed by modified cross-correlation and conventional cross-correlation for comparison. The impacts of the signal-to-noise ratio and time difference of arrival on sound source localization results are demonstrated and discussed. Experimental validation conducted in a non-ideal environment has shown that the modified cross-correlation algorithm can minimize the error in time difference of arrival to be used in sound source localization, thus improving the accuracy in both sound source ranging and direction.

scholarly journals Towards Robust Multiple Blind Source Localization Using Source Separation and Beamforming

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 532
Author(s):  
Henglin Pu ◽  
Chao Cai ◽  
Menglan Hu ◽  
Tianping Deng ◽  
Rong Zheng ◽  
...  
Keyword(s):  
Source Localization ◽  
Sound Source ◽  
Indoor Localization ◽  
Weighting Function ◽  
Signal To Noise Ratio ◽  
Source Separation ◽  
Sound Source Localization ◽  
Angle Of Arrival ◽  
Sound Sources ◽  
Localization Algorithms

Multiple blind sound source localization is the key technology for a myriad of applications such as robotic navigation and indoor localization. However, existing solutions can only locate a few sound sources simultaneously due to the limitation imposed by the number of microphones in an array. To this end, this paper proposes a novel multiple blind sound source localization algorithms using Source seParation and BeamForming (SPBF). Our algorithm overcomes the limitations of existing solutions and can locate more blind sources than the number of microphones in an array. Specifically, we propose a novel microphone layout, enabling salient multiple source separation while still preserving their arrival time information. After then, we perform source localization via beamforming using each demixed source. Such a design allows minimizing mutual interference from different sound sources, thereby enabling finer AoA estimation. To further enhance localization performance, we design a new spectral weighting function that can enhance the signal-to-noise-ratio, allowing a relatively narrow beam and thus finer angle of arrival estimation. Simulation experiments under typical indoor situations demonstrate a maximum of only 4∘ even under up to 14 sources.

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