The introduction of SAS (Synthetic Aperture Sonar) systems has been a game changer for underwater surveys. The gain in resolution, compared to traditional sidescan systems, created a paradigm shift as the information contained in a SAS image switches from shadows to highlights. SAS systems traditionally perform lawnmower type surveys, but the need for multiple views in MCM (Mine-Counter Measure) tasks, for example, opened the interesting problem of target re-acquisition patterns. In particular, circular patterns maximize the aperture, thus the overall image resolution of such system. The capability of CSAS (Circular SAS) has been demonstrated on the field, but the derivation of CSAS processing has not been fully developed. The non-uniform sampling of the circular pattern in particular introduces aberrations within the field of view and a non uniform PSF (Point Spread Function). In this talk, we propose a new spatial sampling scheme which makes the CSAS PSF perfectly uniform. The theoretical closed form solution of the PSF is then derived both in time and Fourier domain. The PSF derivation naturally leads to redefine the image resolution as an energy leakage problem. Thanks to the new sampling scheme and the uniform PSF, we also propose a deconvolution method based on atom waves which increases the CSAS resolution.