A SONAR Simulation used to Develop an Obstacle Avoidance System

Response time to a threat or incident for coastline security is an area needing improvement. Currently, the U.S. Coast Guard is tasked with monitoring the coastal areas using boats or planes, and SCUBA divers are deployed to inspect any potential underwater threats on the coastline or in a port. This can significantly hinder the response time to an incident. A solution to this problem is to use autonomous underwater vehicles (AUVs) to continuously monitor a port. The AUV must be able to navigate the environment without colliding into objects for it to operate effectively. Therefore, an obstacle avoidance system is essential to the activity of the AUV. Conventional underwater vehicles often use imaging or scanning SONARs for obstacle avoidance. The space and power available on a vehicle must be large enough to support these systems. Smaller underwater vehicles may not be able to accommodate a scanning SONAR system for use in obstacle avoidance. Thus, it is of great interest and need to determine the proper configuration of the SONAR system and its corresponding signal processing methods for the coastline security problem. This paper proposes a systematic approach to characterize the OAS performance in terms of environments, obstacles, SONAR configuration and signal processing methods via modeling and simulation. The SONAR simulator is based on modeling a set of circular piston transducers, and the echoes are created based on specular reflections. The ray-tracing algorithm used in the simulation considers reflections from planar, spherical, and cylindrical objects. The main contribution of the presented work is three folded: (1) help us understand better how the return signals are related to the obstacles and environment, (2) help us optimize the complexity of the transducers for coastline obstacle avoidance, and (3) help us better design the avoidance strategy needed for a specific scenario.