Efficient Deconvolution of a Heterogeneous Array Observation Using a Direction-Dependent Point Spread Function

For large aperture arrays like LOFAR and SKA-LOW, the point spread function (PSF) varies significantly across the wide field-of-view (FoV) of these instruments. This turns deconvolution into a computationally demanding and often labour intensive task when using standard algorithms assuming that the PSF is constant over the FoV. In this contribution, we describe an implementation of deconvolution using a direction-dependent (DD) PSF. We demonstrate the advantage of using a DD PSF on an extreme case of a LOFAR observation done with stations of two different sizes. The use of a DD PSF made convergence of deconvolution more robust thereby requiring fewer major cycles and less manual tuning to obtain a good deconvolved image.