Demonstration of passive acoustic detection and tracking of unmanned underwater vehicles
Citable URI
https://hdl.handle.net/1912/10414DOI
10.1575/1912/10414Abstract
In terms of national security, the advancement of unmanned underwater vehicle
(UUV) technology has transformed UUVs from tools for intelligence, surveillance,
and reconnaissance and mine countermeasures to autonomous platforms that can
perform complex tasks like tracking submarines, jamming, and smart mining. Today,
they play a major role in asymmetric warfare, as UUVs have attributes that are
desirable for less-established navies. They are covert, easy to deploy, low-cost, and
low-risk to personnel. The concern of protecting against UUVs of malicious intent is
that existing defense systems fall short in detecting, tracking, and preventing the vehicles
from causing harm. Addressing this gap in technology, this thesis is the first to
demonstrate passively detecting and tracking UUVs in realistic environments strictly
from the vehicle’s self-generated noise. This work contributes the first power spectral
density estimate of an underway micro-UUV, field experiments in a pond and river
detecting a UUV with energy thresholding and spectral filters, and field experiments
in a pond and river tracking a UUV using conventional and adaptive beamforming.
The spectral filters resulted in a probability of detection of 96% and false alarms
of 18% at a distance of 100 m, with boat traffic in a river environment. Tracking
the vehicle with adaptive beamforming resulted in a 6.2±5.7 ∘ absolute difference in
bearing. The principal achievement of this work is to quantify how well a UUV can
be covertly tracked with knowledge of its spectral features. This work can be implemented
into existing passive acoustic surveillance systems and be applied to larger
classes of UUVs, which potentially have louder identifying acoustic signatures.
Description
Submitted in partial fulfillment of the requirements for the degree of Master of Science at the
Massachusetts Institute of Technology
and the
Woods Hole Oceanographic Institution June 2018
Suggested Citation
Thesis: Railey, Kristen E., "Demonstration of passive acoustic detection and tracking of unmanned underwater vehicles", 2018-06, DOI:10.1575/1912/10414, https://hdl.handle.net/1912/10414Related items
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