Sound Source DOA Localization

📍 STM32 Sound Source DOA Localization

An embedded acoustic direction of arrival localization system using a triangular microphone array and an STM32F446RE microcontroller.

📌 Overview

This project determines the direction of an incoming sound source using three microphones arranged in a triangular configuration. By calculating the Time Difference of Arrival (TDOA) of the acoustic signal across each sensor via the GCC-PHAT algorithm, the microcontroller displays the estimated direction on a ring of WS2812B addressable LEDs.

✨ Key Features

• Real-Time Signal Processing: Optimized TDOA estimation using the GCC-PHAT algorithm running on an ARM Cortex-M4 microcontroller.
• Visual Interface: Dynamic directional display using WS2812B addressable LEDs.
• Flexible Power Supply: Dual-power capability supporting both USB and 3 AA battery inputs managed by a low-dropout (LDO) regulator.

🛠️ Hardware Architecture

Complete schematic and PCB layouts KiCad files are available in the Hardware/ directory.

📁 Repository Structure

.
├── Docs/                   # Full schematic PDF
├── Hardware/               # KiCad schematics (.kicad_sch), PCB layout (.kicad_pcb)
├── Media/                  # Photos, videos and 3D renders
├── Software/               # STM32CubeIDE project, drivers, and C source code
├── Tools/                  # Python Signal & GCC-PHAT Plotter
├── .gitignore
├── LICENSE                 # MIT License
└── README.md

⚙️ Building and Flashing

Prerequisites

• STM32CubeIDE
• KiCad (optional, to view or edit hardware design)
• ST-LINK V2/V3 programmer/debugger

Quick Start

1. Clone the repository.
2. Open STM32CubeIDE and import the project from the Software/ subdirectory.
3. Build the project and flash it to the board via ST-LINK.

🖼️ Media

Live Demonstration

💡 Additional photos, 3D renders and PCB layout image can be found in the Media/ directory.

🔍 Debugging & Verification Tools

To validate signal processing and angle calculations, two tools were developed:

• Python Signal & GCC-PHAT Plotter (Tools/): Early test script to visualize signals and cross-correlation results. Used during initial development to plot microphone signals and correlation peaks. Includes two sample text files demonstrating algorithm validation before codebase refactoring.
• Google Sheets and Google Apps Script GCC-PHAT Visualizer: A spreadsheet with extension script to visualize different steps of the GCC-PHAT process. Copy spreadsheet
• Desmos Interactive Geometry: An interactive mathematical model to visualize and verify the sound source coordinates calculations from sensor geometry. View Desmos Model

📄 License

This project is licensed under the MIT License — see the LICENSE file for details.