Seabed Characterization From Ambient Noise Using Short Arrays and Autonomous Vehicles

Reliable SONAR-performance prediction in shallow water requires knowledge of the seabed reflectivity, or its geoacoustic properties, which is expensive and difficult to acquire in situ. This paper illustrates two sea trials conducted in different shallow water areas to investigate the feasibility of acquiring such knowledge efficiently from measurements of naturally occurring ambient noise by an array that is compact enough to be mounted on a small autonomous underwater vehicle. The system relies on a previous technique for passively estimating the bottom reflection loss from the acoustic noise field generated by wind and breaking waves at the sea surface. Results from these experiments supported by numerical modeling are presented and compared with independent measurements of the relevant seabed reflectivity properties. The results obtained from both experiments demonstrate the potential of using autonomous underwater vehicles for seabed characterization.