Multi-modal sensor fusion towards three-dimensional airborne sonar imaging in hydrodynamic conditions

Analogous to how aerial imagery of above-ground environments transformed our understanding of the earth’s landscapes, remote underwater imaging systems could provide us with a dramatically expanded view of the ocean. However, maintaining high-fidelity imaging in the presence of ocean surface waves is a fundamental bottleneck in the real-world deployment of these airborne underwater imaging systems. In this work, we introduce a sensor fusion framework which couples multi-physics airborne sonar imaging with a water surface imager. Accurately mapping the water surface allows us to provide complementary multi-modal inputs to a custom image reconstruction algorithm, which counteracts the otherwise detrimental effects of a hydrodynamic water surface. Using this methodology, we experimentally demonstrate three-dimensional imaging of an underwater target in hydrodynamic conditions through a lab-based proof-of-concept, which marks an important milestone in the development of robust, remote underwater sensing systems.