Abstract: Supervision of technical dives is particularly important in emergency and disaster response operations to ensure the safety of divers in unexplored locations with uncertain conditions. Diver monitoring relies primarily on voice communication and a video stream that gives the operator a first-person view of the diver. However, in many cases underwater visibility can drop to just a few centimeters, leaving the diver only able to feel his way with his hands and the operator depended only on voice communication, making it very difficult for both of them to identify upcoming hazards. In the DeeperSense research project, we are attempting to reduce the limitations caused by poor underwater visibility by using a sonar in combination with an AI-based algorithm designed to translate the sonar signal into a visual image that is independent of the turbidity of the water and gives an overview of the situation where the eye can no longer see anything. Laboratory results show that visual information can be recovered from sonar data.