Source localization using acoustic vector sensor

Direction-of-arrival (DOA) estimation has extensive applications in the field of signal pro-cessing. Most of the work on DOA estimation is done using an array of sensors. But this arrangement is computationally expensive and space consuming. These problems are overcome by using acoustic vector senso...

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Main Author: Mars, Rohith
Other Authors: School of Electrical and Electronic Engineering
Format: Theses and Dissertations
Language:English
Published: 2014
Subjects:
Online Access:http://hdl.handle.net/10356/61631
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-616312023-07-04T15:38:46Z Source localization using acoustic vector sensor Mars, Rohith School of Electrical and Electronic Engineering Andy W. H. Khong DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing Direction-of-arrival (DOA) estimation has extensive applications in the field of signal pro-cessing. Most of the work on DOA estimation is done using an array of sensors. But this arrangement is computationally expensive and space consuming. These problems are overcome by using acoustic vector sensors (AVS). In a real world scenario, the speech signal (where direction has to be estimated) is corrupted by noise, signal reflection and re-verberation. Hence, an estimate of the direction is less accurate. In this dissertation work, existing algorithms for DOA estimation using AVS are discussed. The limitations of these algorithms are analysed and better and more general methods are introduced for DOA es-timation. The work also includes algorithms to denoise the noisy speech signal so that the estimation can be made more accurate. Various algorithms are discussed, compared and analysed using various quantifying parameters for both noisy and denoised speech using MATLAB as simulation tool. Master of Science (Signal Processing) 2014-06-30T04:49:59Z 2014-06-30T04:49:59Z 2014 2014 Thesis http://hdl.handle.net/10356/61631 en 59 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
Mars, Rohith
Source localization using acoustic vector sensor
description Direction-of-arrival (DOA) estimation has extensive applications in the field of signal pro-cessing. Most of the work on DOA estimation is done using an array of sensors. But this arrangement is computationally expensive and space consuming. These problems are overcome by using acoustic vector sensors (AVS). In a real world scenario, the speech signal (where direction has to be estimated) is corrupted by noise, signal reflection and re-verberation. Hence, an estimate of the direction is less accurate. In this dissertation work, existing algorithms for DOA estimation using AVS are discussed. The limitations of these algorithms are analysed and better and more general methods are introduced for DOA es-timation. The work also includes algorithms to denoise the noisy speech signal so that the estimation can be made more accurate. Various algorithms are discussed, compared and analysed using various quantifying parameters for both noisy and denoised speech using MATLAB as simulation tool.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Mars, Rohith
format Theses and Dissertations
author Mars, Rohith
author_sort Mars, Rohith
title Source localization using acoustic vector sensor
title_short Source localization using acoustic vector sensor
title_full Source localization using acoustic vector sensor
title_fullStr Source localization using acoustic vector sensor
title_full_unstemmed Source localization using acoustic vector sensor
title_sort source localization using acoustic vector sensor
publishDate 2014
url http://hdl.handle.net/10356/61631
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