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This work considers the processing of acoustic data from a multibeam 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 an 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, 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. First, a selection of techniques based on the optical flow model is 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 interframe 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 data set and build a high-quality mosaic of the underwater scene.

Attitude-Trajectory Estimation for Forward-Looking Multibeam Sonar Based on Acoustic Image Registration