The Maximal Eigengap Estimator for Acoustic Vector-Sensor Processing
Authors
Bassett, Robert
Foster, Jacob
Gemba, Kay L.
Leary, Paul
Smith, Kevin B.
Subjects
direction of arrival
acoustic vector-sensor
signal subspace
eigengap
acoustic vector-sensor
signal subspace
eigengap
Advisors
Date of Issue
2021-04-21
Date
Publisher
Language
Abstract
This paper introduces the maximal eigengap estimator for finding the direction of arrival of a wideband acoustic
signal using a single vector-sensor. We show that in this setting
narrowband cross-spectral density matrices can be combined in
an optimal weighting that approximately maximizes signal-tonoise ratio across a wide frequency band. The signal subspace
resulting from this optimal combination of narrowband power
matrices defines the maximal eigengap estimator. We discuss the
advantages of the maximal eigengap estimator over competing
methods, and demonstrate its utility in a real-data application
using signals collected in 2019 from an acoustic vector-sensor
deployed in the Monterey Bay.
Type
Article
Description
17 USC 105 interim-entered record; under review.
Series/Report No
Department
Operations Research (OR)
Physics
Organization
Naval Postgraduate School
Identifiers
NPS Report Number
Sponsors
Office of Naval Research
Monterey Bay Aquarium Research Institute (MBARI)
Monterey Bay Aquarium Research Institute (MBARI)
Funder
N0001420WX01523
N0001421WX01634
N0001421WX00410
N0001421WX01634
N0001421WX00410
Format
Citation
Bassett, Robert, et al. "The Maximal Eigengap Estimator for Acoustic Vector-Sensor Processing." arXiv preprint arXiv:2104.10735 (2021).
Distribution Statement
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.