Computational Ocean Acoustics: Propagation Modeling and Sonar Signal Processing

About This Course

This three-week program is designed to give you hands-on experience in computational ocean acoustics. You’ll learn sound propagation modeling and sonar signal processing, gaining an understanding of how sound travels underwater, how acoustic waves can be simulated using computational methods, and how sonar signals are processed for detection, classification, and noise reduction.

The course emphasizes practical application—participants work directly with MATLAB and Python (NumPy, SciPy, Matplotlib, and selected ML tools) using real oceanographic datasets. By the end, you will confidently model underwater sound propagation, analyze sonar data, and understand how these techniques support marine research, environmental monitoring, underwater communication, and exploration.

Aim

This program aims to provide a strong foundation and practical skills in computational ocean acoustics, with a focus on acoustic propagation modeling and sonar signal processing for both research and real-world underwater applications.

Course Objectives

By the end of this course, participants will be able to:

• Understand the fundamentals of ocean acoustics and sound propagation in marine environments
• Model acoustic propagation using Ray, Beam, and Parabolic Equation (PE) methods
• Understand sonar systems and their applications in research and underwater operations
• Apply sonar signal processing techniques for detection, classification, and noise reduction
• Use MATLAB and Python for simulation, modeling, and data analysis
• Explore advanced simulation methods and identify collaboration opportunities across academia and industry

Course Structure

Module 1: Ocean Acoustics Fundamentals and Propagation Modeling

• Why ocean acoustics is important for marine research, monitoring, and exploration
• Sound in water: understanding speed profiles and environmental factors such as temperature, salinity, and depth
• Introduction to sonar: active vs. passive systems and their real-world applications
• Propagation modeling: sound speed variation and modeling approaches (Ray, Beam, PE models)

Hands-on Tools:
MATLAB, Python (NumPy, SciPy), and oceanographic datasets

Module 2: Sonar Systems and Signal Processing for Underwater Data

• Sonar system components: types, configurations, and research/military uses
• Signal processing essentials: detection, classification, and noise reduction
• Advanced DSP: localization and adaptive filtering techniques
• Acoustic measurements: data collection tools and analysis workflows

Hands-on Tools:
Python (SciPy, Matplotlib), signal processing software, acoustic measurement devices/tools (conceptual + workflow-based)

Module 3: Applications, Advanced Simulation, and Research Collaboration

• Sonar applications: environmental monitoring, marine biology, and underwater exploration
• Underwater acoustic communication: modems, transmission challenges, and acoustic networks
• Advanced modeling methods: high-performance simulation using FEM/BEM concepts
• Collaboration pathways: academia–industry–research lab alignment, project design, and use-case mapping

Hands-on Tools:
Python (optionally TensorFlow for ML-based signal analysis), MATLAB, simulation software workflows

Who Should Enrol?

• Marine scientists & researchers working on acoustics, sonar, or environmental monitoring
• Acoustics engineers focused on underwater systems and sonar technology
• Signal processing professionals (DSP, filtering, detection, localization)
• Oceanographers handling acoustic measurements and propagation studies
• Academics & graduate students in marine sciences, acoustics, or ocean engineering
• Industry professionals in sonar, marine exploration, or underwater communication
• Data scientists & ML engineers applying ML to sonar/acoustic signal analysis