Evaluation of vector sensors for adaptive equalization in underwater acoustic communication

Underwater acoustic communication is an extremely complex field that faces many challenges due to the time-varying nature of the ocean environment. Vector sensors are a proven technology that when utilizing their directional sensing capabilities allows us to minimize the effect of interfering noise sources. A traditional pressure sensor array has been the standard for years but suffers at degraded signal to noise ratios (SNR) and requires maneuvers or a lengthly array aperture to direction find. This thesis explores the effect of utilizing a vector sensor array to steer to the direction of signal arrival and the effect it has on equalization of the signal at degraded SNRs. It was demonstrated that utilizing a single vector sensor we were able steer to the direction of arrival and improve the ability of an equalizer to determine the transmitted signal. This improvement was most prominent when the SNR was degraded to levels of 0 and 10 dB where the performance of the vector sensor outperformed that of the pressure sensor in nearly 100% of cases. Finally, this performance improvement occurred with a savings in computational expense.

Department dc:contributor.department

Joint Program in Applied Ocean Physics and Engineering

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2014

Author dc:creator

• Lewis, Matthew Robert, S.M. Massachusetts Institute of Technology

Advisor dc:contributor.advisor

• James C. Preisig.

• Joint Program in Applied Ocean Science and Engineering.
• Mechanical Engineering.
• Woods Hole Oceanographic Institution.

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/1721.1/93793

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/93793