Author Identifier

Mainul Islam Chowdhury: http://orcid.org/0009-0004-9780-9777

Date of Award

2025

Document Type

Thesis - ECU Access Only

Publisher

Edith Cowan University

Degree Name

Master of Engineering Science

School

School of Engineering

First Supervisor

Quoc Viet Phung

Second Supervisor

Iftekhar Ahmad

Abstract

Accurate navigation is essential for underwater vehicles like AUVs, which often operate in deep or remote areas. However, complex ocean dynamics, cumulative inertial-measurement unit (IMU) drift, and diverse noise sources often result in erratic and unreliable position estimates. To overcome these challenges, this thesis presents a method that combines underwater acoustic signals with onboard motion sensor data to improve the underwater position tracking system. The developed system uses a long baseline (LBL) acoustic array of surface buoys to capture the Time-difference-of-Arrival (TDoA) of a multi-pulse beacon. We extract arrival times using a superimposed-envelope-spectrum (SES) detector, which exploits the beacon’s periodic structure to stay reliable even in heavy noise. These acoustic measurements are fused with six-degree-of-freedom IMU data using a particle f ilter (PF). The filter suppresses IMU drift and reveals how long dead-reckoning remains reliable before an acoustic update becomes essential. Simulation results demonstrated that our PF-TDoA fusion method achieved up to 40% reduction in mean localisation error compared to traditional fusion filters under harsh conditions. In our experiment, we compared the simulated IMU prediction with real-world acoustic measurements, and the resulting estimated fused positions remained within a 3m error throughout the experiment, demonstrating robust performance under operational conditions.

Access Note

Access to this thesis is embargoed until 19th December 2026

DOI

10.25958/wsqd-zn84

Download

Available for download on Saturday, December 19, 2026

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