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A new generation of wide-field radio interferometers designed for 21-cmsurveys is being built as drift scan instruments allowing them to observe largefractions of the sky. With large numbers of antennas and frequency channels theenormous instantaneous data rates of these telescopes require novel, efficient,data management and analysis techniques. The $m$-mode formalism exploits theperiodicity of such data with the sidereal day, combined with the assumption ofstatistical isotropy of the sky, to achieve large computational savings andrender optimal analysis methods computationally tractable. We present anextension to that work that allows us to adopt a more realistic sky model andtreat objects such as bright point sources. We develop a linear procedure fordeconvolving maps, using a Wiener filter reconstruction technique, whichsimultaneously allows filtering of these unwanted components. We construct analgorithm, based on the Sherman-Morrison-Woodbury formula, to efficientlyinvert the data covariance matrix, as required for any optimal signal-to-noiseweighting. The performance of our algorithm is demonstrated using simulationsof a cylindrical transit telescope.

An efficient method for removing point sources from full-sky radio interferometric maps