Multiple DOA estimation and blind source separation using estimation-maximization

Yuval Dorfan; Ofer Schwartz; Boaz Schwartz; Emanuël A.P. Habets; Sharon Gannot

doi:10.1109/icsee.2016.7806066

Multiple DOA estimation and blind source separation using estimation-maximization

Yuval Dorfan, Ofer Schwartz, Boaz Schwartz, Emanuël A.P. Habets, Sharon Gannot

Bar-Ilan University - The Alexander Kofkin Faculty of Engineering

Bar-Ilan University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

A blind source separation technique in noisy environment is proposed based on spectral masking and minimum variance distortionless response (MVDR) beamformer (BF). Formulating the maximum-likelihood of the direction of arrivals (DOAs) and solving it using the expectation-maximization, enables the extraction of the masks and the associated MVDR BF as byproducts. The proposed direction of arrival estimator uses an explicit model of the ambient noise, which results in more accurate DOA estimates and good blind source separation. The experimental study demonstrates both the DOA estimation results and the separation capabilities of the proposed method using real room impulse responses in diffuse noise field.

Original language	English
Title of host publication	2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509021529
DOIs	https://doi.org/10.1109/icsee.2016.7806066
State	Published - 4 Jan 2017
Event	2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016 - Eilat, Israel Duration: 16 Nov 2016 → 18 Nov 2016

Publication series

Name	2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016

Conference

Conference	2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016
Country/Territory	Israel
City	Eilat
Period	16/11/16 → 18/11/16

All Science Journal Classification (ASJC) codes

Computer Science Applications
Hardware and Architecture
Artificial Intelligence
Computer Networks and Communications
Electrical and Electronic Engineering

Access to Document

10.1109/icsee.2016.7806066

Cite this

Dorfan, Y., Schwartz, O., Schwartz, B., Habets, E. A. P., & Gannot, S. (2017). Multiple DOA estimation and blind source separation using estimation-maximization. In 2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016 Article 7806066 (2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/icsee.2016.7806066

Dorfan, Yuval ; Schwartz, Ofer ; Schwartz, Boaz et al. / Multiple DOA estimation and blind source separation using estimation-maximization. 2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016. Institute of Electrical and Electronics Engineers Inc., 2017. (2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016).

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abstract = "A blind source separation technique in noisy environment is proposed based on spectral masking and minimum variance distortionless response (MVDR) beamformer (BF). Formulating the maximum-likelihood of the direction of arrivals (DOAs) and solving it using the expectation-maximization, enables the extraction of the masks and the associated MVDR BF as byproducts. The proposed direction of arrival estimator uses an explicit model of the ambient noise, which results in more accurate DOA estimates and good blind source separation. The experimental study demonstrates both the DOA estimation results and the separation capabilities of the proposed method using real room impulse responses in diffuse noise field.",

author = "Yuval Dorfan and Ofer Schwartz and Boaz Schwartz and Habets, {Emanu{\"e}l A.P.} and Sharon Gannot",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016 ; Conference date: 16-11-2016 Through 18-11-2016",

year = "2017",

month = jan,

day = "4",

doi = "10.1109/icsee.2016.7806066",

language = "الإنجليزيّة",

series = "2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Dorfan, Y, Schwartz, O, Schwartz, B, Habets, EAP & Gannot, S 2017, Multiple DOA estimation and blind source separation using estimation-maximization. in 2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016., 7806066, 2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016, Institute of Electrical and Electronics Engineers Inc., 2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016, Eilat, Israel, 16/11/16. https://doi.org/10.1109/icsee.2016.7806066

Multiple DOA estimation and blind source separation using estimation-maximization. / Dorfan, Yuval; Schwartz, Ofer; Schwartz, Boaz et al.
2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016. Institute of Electrical and Electronics Engineers Inc., 2017. 7806066 (2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Multiple DOA estimation and blind source separation using estimation-maximization

AU - Dorfan, Yuval

AU - Schwartz, Ofer

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AU - Habets, Emanuël A.P.

AU - Gannot, Sharon

PY - 2017/1/4

Y1 - 2017/1/4

N2 - A blind source separation technique in noisy environment is proposed based on spectral masking and minimum variance distortionless response (MVDR) beamformer (BF). Formulating the maximum-likelihood of the direction of arrivals (DOAs) and solving it using the expectation-maximization, enables the extraction of the masks and the associated MVDR BF as byproducts. The proposed direction of arrival estimator uses an explicit model of the ambient noise, which results in more accurate DOA estimates and good blind source separation. The experimental study demonstrates both the DOA estimation results and the separation capabilities of the proposed method using real room impulse responses in diffuse noise field.

AB - A blind source separation technique in noisy environment is proposed based on spectral masking and minimum variance distortionless response (MVDR) beamformer (BF). Formulating the maximum-likelihood of the direction of arrivals (DOAs) and solving it using the expectation-maximization, enables the extraction of the masks and the associated MVDR BF as byproducts. The proposed direction of arrival estimator uses an explicit model of the ambient noise, which results in more accurate DOA estimates and good blind source separation. The experimental study demonstrates both the DOA estimation results and the separation capabilities of the proposed method using real room impulse responses in diffuse noise field.

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DO - 10.1109/icsee.2016.7806066

M3 - منشور من مؤتمر

T3 - 2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016

BT - 2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016

Y2 - 16 November 2016 through 18 November 2016

ER -

Dorfan Y, Schwartz O, Schwartz B, Habets EAP, Gannot S. Multiple DOA estimation and blind source separation using estimation-maximization. In 2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016. Institute of Electrical and Electronics Engineers Inc. 2017. 7806066. (2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016). doi: 10.1109/icsee.2016.7806066

Multiple DOA estimation and blind source separation using estimation-maximization

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