Computational Ocean Acoustics: Propagation Modeling and Sonar Signal Processing

About This Course

This three-week program focuses on computational ocean acoustics, with practical training in sound propagation modeling and sonar signal processing. You’ll learn how sound behaves in marine environments, how acoustic waves are modeled using established computational approaches, and how sonar signals are processed for detection, classification, and noise reduction.

The course is highly applied—participants will work hands-on with MATLAB and Python (NumPy, SciPy, Matplotlib, and selected ML tools) using oceanographic datasets and realistic problem scenarios. By the end of the program, you’ll be able to model underwater sound propagation, analyze sonar data, and understand how these methods support marine research, environmental monitoring, underwater communication, and exploration.

Aim

The aim of this program is to equip participants with strong foundations and practical skills in computational ocean acoustics, with a focus on acoustic propagation modeling and sonar signal processing for marine research and real-world underwater applications.

Course Objectives

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

• Understand ocean acoustics fundamentals and sound propagation in marine environments

• Model acoustic propagation using Ray, Beam, and Parabolic Equation (PE) approaches

• Understand sonar systems and how they are used in marine research and underwater operations

• Apply sonar signal processing techniques for detection, classification, and noise reduction

• Use MATLAB and Python for acoustic modeling, simulation, 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 matters: marine research, monitoring, and exploration

• Sound in water: sound speed profiles and environmental factors (temperature, salinity, depth)

• Intro to sonar: active vs. passive systems and real-world applications

• Propagation modeling: sound speed variation and modeling approaches (Ray, Beam, PE models)

Hands-on Tools:
MATLAB, Python (NumPy, SciPy), 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, 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?

This program is ideal for:

• 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, ocean engineering

• Industry professionals in sonar, marine exploration, underwater communication

• Data scientists & ML engineers applying ML to sonar/acoustic signal analysis