Acoustic and seismic signal processing for footsetp detection

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.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2006

Author dc:creator

• Bland, Ross E. (Ross Edward)

Advisor dc:contributor.advisor

• Charles E. Rohrs.

• Electrical Engineering and Computer Science.

Statement dc:rights

• 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.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/37052

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/37052