• DocumentCode
    178759
  • Title

    Gridless compressive sensing

  • Author

    Panahi, A. ; Viberg, M.

  • Author_Institution
    Dept. of Signals & Syst., Chalmers Univ. of Technol., Gothenburg, Sweden
  • fYear
    2014
  • fDate
    4-9 May 2014
  • Firstpage
    3385
  • Lastpage
    3389
  • Abstract
    The effect of off-grid atoms has become the prominent problem in application of the Compressed Sensing (CS) techniques to the cases where there is an underlying continuous parametrization. In this work, we develop a generalizing CS framework which shows that sampling to a finite grid is not necessary toward compressive estimation. We propose an alternative procedure over infinite dictionaries, which we show to be theoretically consistent in many cases of interest and then propose a robust implementation. We illustrate the general properties of our technique in some difficult practical instances of frequency estimation.
  • Keywords
    compressed sensing; frequency estimation; signal sampling; CS framework; compressive estimation; frequency estimation; gridless compressive sensing; infinite dictionaries; off-grid atoms; Compressed sensing; Convex functions; Dictionaries; Estimation; Signal to noise ratio; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
  • Conference_Location
    Florence
  • Type

    conf

  • DOI
    10.1109/ICASSP.2014.6854228
  • Filename
    6854228