Acoustic Triangulation

Project Overview

Acoustic triangulation is a technique used to locate the source of a sound by analyzing sound waves received at multiple sensors or microphones. This method relies on measuring the time differences of sound arrival (TDoA) at various points and using these differences to calculate the sound source's position. The significance of acoustic triangulation lies in its wide range of applications, it aids in navigation, ranging and tracking. The technology's ability to provide non-visual localization makes it valuable in diverse fields, from military applications to entertainment and virtual reality, demonstrating its versatility and importance in modern technological advancements.

Objectives

  • Triangulate a sound source by calculating its 2D coordinates on a grid using Time Difference of Arrival (TDoA) algorithms.
  • Display the triangulation result: Show the calculated position on a graphical user interface (GUI).
  • Record data from each microphone simultaneously. The system should capture audio from all four microphones simultaneously.
  • Implement noise reduction: Filter and process the captured audio to reduce noise interference.

Project Constraints

  • Must only use 2 Raspberry Pi zero and 4 microphones.
  • Must use TDoA to triangulate the sound source: TDoA methods require accurate time synchronization between the microphones.

Project Details

The project involves the following tasks:

  1. Analyzing requirements, specifications, and constraints.
  2. Creating a paper design.
  3. Conducting simulations.
  4. Experimental implementation.
  5. Full system implementation.

Outcomes and Results

  • Successfully developed a robust Acoustic Localization system meeting most of the Acceptance Test Procedures (ATPs).
  • Extensive simulations provided valuable insights for refining triangulation algorithms, sound detection, GUI usability, and code functionality.
  • Experimental implementation addressed real-world challenges such as environmental noise and Raspberry Pi synchronization.
  • The system demonstrated accurate and effective source position estimation in most scenarios.
  • Performance was affected by additional environmental noise, particularly human speech.
  • Identified areas for future improvement, including enhanced synchronization, optimized frequency range, and error detection and correction.

Project Document

For more detailed information, you can view the full project document here:

View the Project Document (PDF)