Forward-Looking Sonar Simulation Model for Robotic Applications

Abstract

Underwater simulators are less common due to the complexity of underwater acoustics. Simulation is an effective tool for rapid testing of autonomous vehicles and complements the test and evaluation process. The goal of this thesis is to present a computationally efficient forward-looking sonar simulation model for robotic applications. A model for a single sonar beam is developed using a point-scattering model, applying both Fourier synthesis and a correction for beam forming. The single sonar beams are concatenated to simulate a forward-looking sonar system field of view. The result is a sonar simulation model that can be used in the established ROS Gazebo robotic framework as a tool for effective testing of autonomous underwater vehicles. Future improvements in the acoustics of the sonar model include the addition of reverberation, multi-path propagation, and interference.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2020
Accession Number
AD1126563

Entities

People

  • Andreina Rascon

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Autonomy
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Acoustic Phenomena
  • Acoustic Propagation
  • Acoustic Properties
  • Acoustic Waves
  • Acoustics
  • Active Sonar
  • Autonomous Underwater Vehicles
  • Autonomous Vehicles
  • Beam Forming
  • Control Systems
  • Graphics Processing Unit
  • Reflection
  • Scattering
  • Simulators
  • Sonar
  • Test And Evaluation
  • Three Dimensional
  • Two Dimensional
  • Underwater Acoustics
  • Underwater Vehicles
  • United States
  • Unmanned Underwater Vehicles
  • Unmanned Vehicles

Fields of Study

  • Engineering

Readers

  • Acoustical Oceanography.
  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Computational Modeling and Simulation

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Bayesian Inference
  • Autonomy