Source cancellation in cross-correlation functions for broadband multisource DOA estimation

Diaz-Guerra, David; Beltrán, José Ramón

doi:10.1016/j.sigpro.2019.107442

Cited by 5 publications

(3 citation statements)

References 29 publications

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“…Different approaches have been previously proposed to improve the localization of multiple sources under an SRP framework, with examples including the use of postprocessing steps [9][10][11][12], clustering techniques [13][14][15] and sparsity-based modeling of SRP maps [16]. In the latter case, the observed broadband SRP map is modeled as a linear combination of basis functions describing ideal SRP maps, weighted by coefficients associated to each candidate source location.…”

Section: Introductionmentioning

confidence: 99%

Multi-Source Direction-of-Arrival Estimation using Group-Sparse Fitting of Steered Response Power Maps

Tengan,

Dietzen,

Elvander

et al. 2023

2023 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)

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In this paper, a method is proposed for estimating the direction of arrival (DOA) of multiple broadband sound sources by solving a group-sparse optimization problem. A steered response power (SRP) map is modeled using power spectral densities (PSDs) defined on an overcomplete grid of candidate DOAs. The source DOAs are then estimated as the directions corresponding to the largest peaks of the frequency-averaged PSDs. The proposed optimization problem is iteratively solved using the alternating direction method of multipliers (ADMM), and simulation results show that the proposed method overall outperforms the frequency-domain sparse iterative covariance-based estimation (SPICE) method and performs better than or similar to the conventional SRP-PHAT method for varying levels of noise and reverberation.

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Section: Introductionmentioning

confidence: 99%

Multi-Source Direction-of-Arrival Estimation using Group-Sparse Fitting of Steered Response Power Maps

Tengan,

Dietzen,

Elvander

et al. 2023

2023 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)

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“…For TDOA-based localization, the first step is precise determination of the arrival times of a sound source at the microphones, and then the differences in arrival times can be determined using correlation functions. Secondly, The AOAs measurements are derived to obtain the sound source location [31]. In this context, several mathematical approaches have been adopted to improve the DOA.…”

Section: Introductionmentioning

confidence: 99%

“…The experiments conducted can be used as robust graduate and undergraduate exercises in fields such as mechanical engineering, computer application, electronic engineering, engineering physics. Through the cross-correlation (CC) function and in order to detect the received sound waves, we have to be able to detect the time difference in TOA [31]. When the first microphone of one of the two pairs detects the sound source, the second microphone detects the same sound source after a shifted-time.…”

Section: Introductionmentioning

confidence: 99%

A laboratory experiment for real-time sound source localization using Microsoft Kinect for Xbox 360

Douaer

2022

Preprint

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Sound Source Localization (SSL) consists of estimating the position of an emitting sound source. Accurate SSL is an essential step in many research areas as well as practical applications in acoustic signal processing and wireless communications. The main contribution of this work is the simplification of the high performance of two-dimensional sound source localization (2D-SSL), in which only four microphones are required. Firstly, the Time Difference Of Arrival (TDOA) based method is applied to a linear array configuration of four acquisition USB microphones, which have been used in two pairs to mount the experimental setup. For each single pair, the Angle of Arrival (AOA) of the sound source is calculated. Then, the 2D-SSL is determined using the trigonometric identities. To implement such a schematic, we have used the microphone array incorporated into the Microsoft Kinect device to acquire sound waves in real-time. To validate the accuracy of our study, laboratory experiments of sound source localization at different sound intensity levels were performed. In terms of RMSE position, the experimental results indicate that the suggested solution can be used to accurately find a two-dimensional sound source location in the far-field.

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Robust Sound Source Tracking Using SRP-PHAT and 3D Convolutional Neural Networks

Diaz-Guerra

Miguel

Beltrán

2021

IEEE/ACM Trans. Audio Speech Lang. Process.

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Source cancellation in cross-correlation functions for broadband multisource DOA estimation

Cited by 5 publications

References 29 publications

Multi-Source Direction-of-Arrival Estimation using Group-Sparse Fitting of Steered Response Power Maps

Multi-Source Direction-of-Arrival Estimation using Group-Sparse Fitting of Steered Response Power Maps

A laboratory experiment for real-time sound source localization using Microsoft Kinect for Xbox 360

Robust Sound Source Tracking Using SRP-PHAT and 3D Convolutional Neural Networks

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