Benchmarking acoustic underwater sensor-node localization against seafloor photogrammetry

Acoustic ranging is the established approach for localizing seafloor sensor nodes and generally achieves high precision. However, performance evaluation typically relies on the same acoustic ranges and GNSS positions used during localization, making error estimates self-referential. We address this circularity by introducing a photogrammetric benchmark, georeferenced by a ship-based USBL system, that is constructed independently of the acoustic ranges and GNSS positions under evaluation. For a five-node acoustic sensor network deployed at 60m depth offshore Santorini, Greece, we build a georeferenced photo mosaic of the deployment area using a ship-towed camera sled and extract relative node positions at centimeter-scale precision. We then compare three established localization algorithms, a centralized least-squares solver and two distributed approaches based on the extended Kalman filter and belief propagation, against this reference. All algorithms achieve relative accuracy below 2 m. The centralized least-squares approach outperforms the distributed approaches by more than 1 m. This demonstrates that the benchmark is sensitive enough to evaluate the performance of different algorithms, offering a path toward noncircular evaluation of underwater localization systems.

Content

Subjects

underwater

acoustics

localization

photogrammetry

DDC Class

551: Geology, Hydrology Meteorology

004: Computer Sciences