Low frequency array (lofar)- potential and challenges

Marinus Jan Bentum, A.W. Gunst, A.J. Boonstra

    Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

    Abstract

    The Low Frequency Array (LOFAR) is a large radio telescope based on phased array principles, distributed over several European countries with its central core in the Northern part of the Netherlands. LOFAR is optimized for detecting astronomical signals in the 30-80 MHz and 120 240 MHz frequency window. LOFAR detects the incoming radio signals by using an array of simple omni-directional antennas. The antennas are grouped in so called stations mainly to reduce the amount of data generated. More than forty stations will be built, mainly within a circle of 150 kilometres in diameter. But LOFAR stations will also be built in other European countries. The signals of all the stations are transported to the central processor facility, where all the station signals are correlated with each other, prior to imaging. In this chapter the signal processing aspects on system level will be presented. Methods to image the sky will be given and the mapping of these concepts to the LOFAR phase array radio telescope will be presented. Challenges will be addressed and potentials for further research will be presented.
    Original languageUndefined
    Title of host publicationApplied Signal and Image Processing: Multidisciplinary Advancements
    EditorsEvor Hines, Rami Qahwaji, Roger Green
    Place of PublicationUSA
    PublisherIGI Global
    Pages1-18
    Number of pages18
    ISBN (Print)978-1-60960-477-6
    Publication statusPublished - 31 Aug 2010

    Publication series

    Name
    PublisherIGI Global

    Keywords

    • IR-75322
    • METIS-276193
    • Beam-forming
    • Phased array
    • low-frequency astronomy
    • Correlation
    • EWI-19009
    • digital signal processing
    • Radio astronomy

    Cite this

    Bentum, M. J., Gunst, A. W., & Boonstra, A. J. (2010). Low frequency array (lofar)- potential and challenges. In E. Hines, R. Qahwaji, & R. Green (Eds.), Applied Signal and Image Processing: Multidisciplinary Advancements (pp. 1-18). USA: IGI Global.