Acoustic and seismic signal processing for footsetp detection
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2007
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| Online Access: | http://hdl.handle.net/1721.1/37052 |
| _version_ | 1811086689133658112 |
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| author | Bland, Ross E. (Ross Edward) |
| author2 | Charles E. Rohrs. |
| author_facet | Charles E. Rohrs. Bland, Ross E. (Ross Edward) |
| author_sort | Bland, Ross E. (Ross Edward) |
| collection | MIT |
| description | Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006. |
| first_indexed | 2024-09-23T13:30:24Z |
| format | Thesis |
| id | mit-1721.1/37052 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T13:30:24Z |
| publishDate | 2007 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/370522019-04-11T05:54:56Z Acoustic and seismic signal processing for footsetp detection Bland, Ross E. (Ross Edward) Charles E. Rohrs. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006. Includes bibliographical references (leaves 83-84). The problem of detecting footsteps using acoustic and seismic sensors is approached from three different angles in this thesis. First, accelerometer data processing systems are designed to make footsteps more apparent to a human operator listening to accelerometer recordings. These systems work by modulating footstep signal energy into the ear's most sensitive frequency bands. Second, linear predictive modeling is shown to be an effective means to detect footsteps in accelerometer and microphone data. The time evolution of the third order linear prediction coefficients leads to the classical binary hypothesis testing framework. Lastly, a new method for blindly estimating the filters of a SIMO channel is presented. This method is attractive because it allows for a more tractable performance analysis. by Ross E. Bland. M.Eng. 2007-04-03T17:06:05Z 2007-04-03T17:06:05Z 2006 2006 Thesis http://hdl.handle.net/1721.1/37052 79629647 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 84 leaves application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Bland, Ross E. (Ross Edward) Acoustic and seismic signal processing for footsetp detection |
| title | Acoustic and seismic signal processing for footsetp detection |
| title_full | Acoustic and seismic signal processing for footsetp detection |
| title_fullStr | Acoustic and seismic signal processing for footsetp detection |
| title_full_unstemmed | Acoustic and seismic signal processing for footsetp detection |
| title_short | Acoustic and seismic signal processing for footsetp detection |
| title_sort | acoustic and seismic signal processing for footsetp detection |
| topic | Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/37052 |
| work_keys_str_mv | AT blandrosserossedward acousticandseismicsignalprocessingforfootsetpdetection |