Motion-Based Compression of Underwater Video Imagery for the Operations of Unmanned submersible Vehicles

In this paper we present a methodology for very high resolution acoustic mapping from an underwater vehicle. Based on the navigation, attitude, and bathymetric sensors that currently exist we show that the major issues for underwater mapping involve modeling sonar-specific artefacts due to beam pattern effects, calibration offsets of attitude sensors, and estimation and correction of tidal influences. We present an algorithm for modeling the beam pattern and for estimating calibration errors based upon specific vehicle maneuvers. Using a 675-kHz mechanically scanned pencilbeam sonar mounted on the Jason ROV, mapping results from an archaeological site at water depth 800m in the Mediterranean are presented that are seen to be consistent and independently verifiable.