Geometric Correction of Underwater Forward Looking Sonar-Based 3-D Reconstruction Via PS-Based Slope Pattern Interpretation Using AUV

Abstract

Forward-looking sonar (FLS) enables long-range underwater sensing. In FLS-based 3-D reconstruction, falsely inclined surfaces arise from elevation ambiguity caused by the finite vertical beamwidth. Existing approaches mitigate these errors using multi-pass strategies, but they require repeated observations, which are often impractical in real-world underwater operations. To address this, we propose a pattern-informed geometric refinement framework that leverages structural patterns from profiling sonar (PS) to resolve ambiguity in FLS-based reconstruction. Within this framework, geometric patterns within ambiguity-dominated intervals are analyzed to distinguish between physically valid surfaces and falsely inclined surfaces, and selective geometric refinement is applied accordingly. Experimental results demonstrate effective suppression of falsely inclined surfaces and improved reconstruction accuracy without trajectory modifications. This provides a practical solution for reliable 3-D mapping and perception in underwater robotic applications.