Abstract
It is a long-held notion that medium-induced signal fluctuations render long-range synthetic aperture sonar (SAS) imaging unfeasible. Recent experimental results in shallow water, however, indicate that near-theoretical SAS performance can be achieved with the aid of (sonar data driven) motion compensation and autofocus algorithms, even for surface- and bottom-reflected paths. This study examined in detail the role of these adaptive compensation algorithms in overcoming rough surface scattering-induced phase errors. Imaging and compensation algorithms were applied to sonar data that was numerically modeled for moderate to severe surface conditions. We report here the predicted imaging performance as a function of surface conditions and grazing angles. [Work supported by the Office of Naval Research.]
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