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Massachusetts Institute of Technology

Advances in Passive Acoustic Detection, Localization, and Tracking Applied to Unmanned Underwater Vehicles

Abstract

dc:description.abstract

Detection, classification, localization, and tracking (DCLT) of unmanned underwater vehicles (UUVs) in the presence of shipping traffic is a critical task for passive acoustic harbor security systems. In general, vessels can be tracked by their unique acoustic signature due to machinery vibration and cavitation noise. However, cavitation noise of UUVs is considerably quieter than ships and boats, making detection significantly more challenging. In this thesis, I demonstrated that it is possible to passively track a UUV from its high-frequency motor noise using a stationary array in shallow-water experiments with passing boats. First, causes of high frequency tones were determined through direct measurements of two UUVs at a range of speeds. From this analysis, common and dominant features of noise were established: strong tones at the motor’s pulse-width modulated frequency and its harmonics. From the unique acoustic signature of the motor, I derived a high-precision, remote sensing method for estimating propeller rotation rate. In shallow-water UUV field experiments, I demonstrated that detecting a UUV from motor noise, in comparison to broadband noise from the vehicle, reduces false alarms from 45% to 8.4% for 90% true detections. Beamforming on the motor noise, in comparison to broadband noise, improved the bearing accuracy by a factor of 3.2×. Because the signal is also high-frequency, the Doppler effect on motor noise is observable and I demonstrate that range rate can be measured. Furthermore, measuring motor noise was a superior method to the “detection of envelope modulation on noise” algorithm for estimating the propeller rotation rate. Extrapolating multiple measurements from the motor signature is significant because Bearing-DopplerRPM measurements outperform traditional bearing-Doppler target motion analysis. In the unscented Kalman filter implementation, the tracking solution accuracy for bearing, bearing rate, range, and range rate improved by a factor 2.2×, 15.8×, 3.1×, and 6.2× respectively. These findings are significant for improving UUV localization and tracking, and for informing the next-generation of quiet UUV propulsion systems.

Degree

thesis:*
Name thesis:degree_name
Doctoral
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2022

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Kita, Kristen Railey
Advisors dc:contributor.advisor
  • Schmidt, Henrik
  • DiBiaso, Dino

Rights

dc:rights
Statement dc:rights
  • In Copyright - Educational Use Permitted
  • Copyright retained by author(s)

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1721.1/143395
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/143395

Chain of custody

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

Kita, Kristen Railey. Advances in Passive Acoustic Detection, Localization, and Tracking Applied to Unmanned Underwater Vehicles. Massachusetts Institute of Technology, 2022. https://hdl.handle.net/1721.1/143395