Acoustic vector-sensor array processing
Name
679645164-MIT.pdf
Description
Full printable version
Size
1.49 MB
Format
Adobe PDF
Checksum (MD5)
a681225bf820901bb3fbde20fa0095da
Author(s)
Kitchens, Jonathan Paul
Advisor(s)
Arthur B. Baggeroer.
Date Issued
2010
Publisher
Massachusetts Institute of Technology
Abstract
Existing theory yields useful performance criteria and processing techniques for acoustic pressure-sensor arrays. Acoustic vector-sensor arrays, which measure particle velocity and pressure, offer significant potential but require fundamental changes to algorithms and performance assessment. This thesis develops new analysis and processing techniques for acoustic vector-sensor arrays. First, the thesis establishes performance metrics suitable for vector sensor processing. Two novel performance bounds define optimality and explore the limits of vector-sensor capabilities. Second, the thesis designs non-adaptive array weights that perform well when interference is weak. Obtained using convex optimization, these weights substantially improve conventional processing and remain robust to modeling errors. Third, the thesis develops subspace techniques that enable near-optimal adaptive processing. Subspace processing reduces the problem dimension, improving convergence or shortening training time.
Description
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student submitted PDF version of thesis.
Includes bibliographical references (p. 145-148).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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