Acoustic source localization
Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2016.
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| Other Authors: | |
| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2016
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| Online Access: | http://hdl.handle.net/1721.1/104271 |
| _version_ | 1811072821441331200 |
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| author | Zhao, Nilu |
| author2 | George Barbastathis. |
| author_facet | George Barbastathis. Zhao, Nilu |
| author_sort | Zhao, Nilu |
| collection | MIT |
| description | Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2016. |
| first_indexed | 2024-09-23T09:15:21Z |
| format | Thesis |
| id | mit-1721.1/104271 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T09:15:21Z |
| publishDate | 2016 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1042712019-04-12T16:18:42Z Acoustic source localization Zhao, Nilu George Barbastathis. Massachusetts Institute of Technology. Department of Mechanical Engineering. Massachusetts Institute of Technology. Department of Mechanical Engineering. Mechanical Engineering. Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2016. Cataloged from PDF version of thesis. Includes bibliographical references (pages 59-61). Many technologies rely on underwater acoustics. Most of these applications are able to denoise Gaussian noise from the surrounding, but have trouble removing impulse like noises. One source of impulse-like noise is the snapping shrimps. The acoustic signals they emit from snapping their claws hinder technologies, but can also be used as a source of ambient noise illumination due to the rough uniformity in their spatial distribution. Understanding the spatial distributions of these acoustic signals can be useful in working to mitigate or amplify their effects. Our collaborators in Singapore use a multi-array sensor to take measurements of the sound pressures of the environment in the ocean. This thesis investigates in solving the signal reconstruction problem -- given the measurements, reconstruct the locations of the original signal sources. A numerical model for the system consisting of the snapping shrimp signals, the environment, and the sensor is formulated. Three methods of reconstruction -- Disciplined Convex Programming, Orthogonal Matching Pursuit, and Compressive Sensing -- are explored, and their robustness to noise, and sparsity are examined in simulation. Results show that Two-Step Iterative Shrinkage Threshold (TwIST) is the most robust to noisy and non-sparse signals. The three methods were then tested on real data set, in which OMP and TwIST showed promising consistency in their results, while CVX was unable to converge. Since there is no available information on ground truth, the consistency is a promising result. by Nilu Zhao. S.M. 2016-09-13T19:19:48Z 2016-09-13T19:19:48Z 2016 2016 Thesis http://hdl.handle.net/1721.1/104271 958161257 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 61 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Mechanical Engineering. Zhao, Nilu Acoustic source localization |
| title | Acoustic source localization |
| title_full | Acoustic source localization |
| title_fullStr | Acoustic source localization |
| title_full_unstemmed | Acoustic source localization |
| title_short | Acoustic source localization |
| title_sort | acoustic source localization |
| topic | Mechanical Engineering. |
| url | http://hdl.handle.net/1721.1/104271 |
| work_keys_str_mv | AT zhaonilu acousticsourcelocalization |