The H i Parkes All Sky Survey: southern observations, calibration and robust imaging |
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| Institution: | Australia Telescope National Facility, CSIRO, PO Box 76, Epping, NSW 1710, Australia;Centre for Astrophysics and Supercomputing, Swinburne University of Technology, PO Box 218, Hawthorn, VIC 3122, Australia;Netherlands Foundation for Research in Astronomy, PO Box 2, 7990 AA Dwingeloo, the Netherlands;Department of Physics and Astronomy, University of Leicester, Leicester LE1 7RH;Department of Physics and Astronomy, University of Wales, Cardiff CF24 3YB;Department of Physics, University of Western Sydney Macarthur, Campbelltown, NSW 2560, Australia;Department of Physics, University of Bristol, Tyndall Avenue, Bristol BS8 1TL;School of Physics, University of Melbourne, VIC 3010, Australia;Research School of Astronomy and Astrophysics, Australian National University, Weston Creek, ACT 2611, Australia;School of Physics, University of Sydney, NSW 2006, Australia;Institute for Astrophysics, University of New Mexico, Albuquerque, NM 87131, USA;Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218, USA;Departamento de Astronomia, Universidad de Guanajuato, Guanajuato, GTO 36000, Mexico;Anglo Australian Observatory, PO Box 296, Epping, NSW 1710, Australia;Observatoire de la Côte d'Azur, Nice, 06304 Nice Cedex 4, France |
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| Abstract: | The acquisition of H i Parkes All Sky Survey (HIPASS) southern sky data commenced at the Australia Telescope National Facility's Parkes 64-m telescope in 1997 February, and was completed in 2000 March. HIPASS is the deepest H i survey yet of the sky south of declination +2°, and is sensitive to emission out to 170 h75?1 Mpc. The characteristic root mean square noise in the survey images is 13.3 mJy. This paper describes the survey observations, which comprise 23 020 eight-degree scans of 9-min duration, and details the techniques used to calibrate and image the data. The processing algorithms are successfully designed to be statistically robust to the presence of interference signals, and are particular to imaging point (or nearly point) sources. Specifically, a major improvement in image quality is obtained by designing a median-gridding algorithm which uses the median estimator in place of the mean estimator. |
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| Keywords: | instrumentation: detectors methods: observational methods: statistical techniques: image processing surveys radio lines: galaxies |
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