On optimal AUV track-spacing for underwater mine detection

Abstract

This work addresses the task of designing the optimal survey route that an autonomous underwater vehicle (AUV) should take in mine countermeasures (MCM) operations. It is assumed that the AUV is equipped with a side-looking sonar that is capable of generating high-resolution imagery of the underwater environment. The objective of the path-planning task is framed in terms of maximizing the success of detecting underwater mines in such imagery. Several commonly made - but inaccurate - assumptions about the problem are raised and refuted; it is demonstrated that mine detection performance depends on both range and seabed type. The issue of how to update detection probabilities when multiple views are obtained is also addressed. These various considerations are exploited in conjunction with synthetic aperture sonar (SAS) data to predict detection performance and efficiently design AUV routes that outperform standard ladder surveys. The proposed algorithm can be used to assess and quantify detection performance achieved in past, as well as future, missions. Because the entire route of the AUV can still be designed before deployment, no additional onboard processing or adaptive capabilities are required of the AUV. Therefore, the proposed approach can be immediately applied to systems conducting MCM operations at sea. The method is demonstrated on real SAS imagery collected by an AUV in the Baltic Sea.