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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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 |
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DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing Mars, Rohith Source localization using acoustic vector sensor |
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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. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Mars, Rohith |
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Theses and Dissertations |
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Mars, Rohith |
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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 |
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Source localization using acoustic vector sensor |
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Source localization using acoustic vector sensor |
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source localization using acoustic vector sensor |
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2014 |
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http://hdl.handle.net/10356/61631 |
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1772828440146214912 |