SURFACE VESSEL ACOUSTIC SIGNAL DIRECTION OF ARRIVAL ESTIMATION BY VECTOR SENSOR PROCESSING WITH THE MAXIMUM EIGENGAP ESTIMATOR
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Authors
Foster, Jacob W.
Subjects
hydrophone
localization
machine learning
underwater acoustics
covariance matrix
tensor decomposition
vector sensor
localization
machine learning
underwater acoustics
covariance matrix
tensor decomposition
vector sensor
Advisors
Leary, Paul
Bassett, Robert L.
Date of Issue
2021-06
Date
Publisher
Monterey, CA; Naval Postgraduate School
Language
Abstract
This work intends to improve Navy/Marine Corps reconnaissance capabilities for operations in near-shore–contested amphibious environments. We present a novel unsupervised approach to vessel localization, the maximum eigengap estimator, by analyzing the multi-directional signal channels from a single vector sensor connected to the cabled observatory operated by the Monterey Bay Aquarium Research Institute–Monterey Accelerated Research System (MBARI-MARS). This work postulates that the direction of arrival and frequency of a vessel source signal can be identified by optimizing the weights over the aggregated cross-power spectral density matrices of a vector sensor’s directional channels. We explore the accuracy of the maximum eigengap estimator’s performance with various upper and lower bounds for frequency selection, and by changing source distance and direction to the sensor, and against multi-source scenarios. The estimator shows agreement with the physics-informed Bellhop ray model and produces accurate estimations for direction of arrival for single-source estimations within a 12-kilometer range from the sensor. We also demonstrate the novelty of the algorithm to produce automatic selection of source frequency.
Type
Thesis
Description
Series/Report No
Department
Operations Research (OR)
Organization
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NPS Report Number
Sponsors
Funder
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Citation
Distribution Statement
Approved for public release. Distribution is unlimited.
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.