Attitude-trajectory estimation for forward looking multi-beam sonar based on acoustic image registration

This work considers the processing of acoustic data from a multi-beam Forward Looking Sonar (FLS) on a moving underwater platform to estimate the platform’s attitude and trajectory. We propose an algorithm to produce an estimate of the attitude-trajectory for a FLS based on the optical flow between consecutive sonar frames. The attitude-trajectory can be used to locate an underwater platform, such as an Autonomous Underwater Vehicle (AUV), to a degree of accuracy suitable for navigation. It can also be used to build a mosaic of the underwater scene. The estimation is performed in three steps. Firstly, a selection of techniques based on the optical flow model are used to estimate a pixel displacement map (DM) between consecutive sonar frames represented in the native polar (range/bearing) format. The second step finds the best match between the estimated DM and DMs for a set of modeled sonar sensor motions. To reduce complexity, it is proposed to describe the DM with a small parameter vector derived from the displacement distribution. Thus, an estimate of the incremental sensor motion between frames is made. Finally, using a weighted regularized spline technique, the incremental inter-frame motions are integrated into an attitude-trajectory for the sonar sensor. To assess the accuracy of the attitude-trajectory estimate, it is used to register FLS frames from a field experiment dataset and build a high-quality mosaic of the underwater scene.