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Massachusetts Institute of Technology

Robust vector sensor array processing and performance analysis

Abstract

dc:description.abstract

Acoustic vector sensors, which measure scalar pressure along with particle motion (a vector quantity), feature many advantages over omnidirectional hydrophone sensors. A sizable literature exists on the theory of processing signals for many vector sensor array applications. In practice, however, mismatch (the difference between the assumed and actual system configurations), several noise processes and low sample support can pose significant problems. Processing techniques should be robust to these system imperfections and practical complexities. This thesis presents analytical results which quantify the effect of system mismatch and low sample support on acoustic vector sensor array performance. All arrays are susceptible to perturbations in array element locations; vector sensor arrays, however, are also sensitive to changes in sensor orientation. This is due to the fact that the particle motion vector measurement must be placed in a global reference frame. Gilbert and Morgan (1955) developed a statistical analysis with system mismatch for an array of scalar, omnidirectional elements. This thesis includes a vector sensor extension to their analysis by including sensor orientation perturbations. Theoretical expressions for the mean and variance of the vector sensor array spatial response are derived using a Gaussian perturbation model, with excellent comparisons between theory and simulation. Such analysis leads to insight into theoretical limits of both conventional and adaptive processing in the presence of system imperfections. One noteworthy result is that the vector aspect of the array "dampens" the effect of array mismatch, enabling deeper true nulls. This is accomplished because the variance of the vector sensor array spatial response (due to rotational, positional and filter gain/phase perturbations) decreases in the side lobes, unlike arrays of omnidirectional hydrophones.

Degree

thesis:*
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
2009

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Poulsen, Andrew Joseph
Advisor dc:contributor.advisor
  • Arthur B. Baggeroer.

Subjects

dc:subject × 1

Rights

dc:rights
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.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/47751
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/47751

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Poulsen, Andrew Joseph. Robust vector sensor array processing and performance analysis. Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/47751