• DocumentCode
    2924622
  • Title

    Compressive angular and frequency periodogram reconstruction for multiband signals

  • Author

    Ariananda, Dyonisius Dony ; Romero, Daniel ; Leus, Geert

  • Author_Institution
    Fac. of EEMCS, Delft Univ. of Technol., Delft, Netherlands
  • fYear
    2013
  • fDate
    15-18 Dec. 2013
  • Firstpage
    440
  • Lastpage
    443
  • Abstract
    In this paper, we present a duality between two problems: the reconstruction of the angular periodogram from spatial-domain signals received at different time indices and that of the frequency periodogram from time-domain signals received at different wireless sensors. We assume the existence of a multiband structure in either the angular or frequency domain representation of the received spatial or time-domain signal, respectively, where different bands are assumed to be uncorrelated. The two problems lead to a similar circulant structure in the so-called coset correlation matrix, which allows for a strong compression and a least-squares (LS) reconstruction approach. The LS reconstruction of the periodogram is possible under the full column rank condition of the system matrix, which is achievable by designing the spatial or temporal sampling patterns based on a circular sparse ruler.
  • Keywords
    correlation methods; frequency-domain analysis; least squares approximations; matrix algebra; signal reconstruction; signal representation; signal sampling; time-domain analysis; LS reconstruction; angular domain representation; circulant structure; circular sparse ruler; compressive angular periodogram reconstruction; coset correlation matrix; frequency domain representation; frequency periodogram reconstruction; least-squares reconstruction approach; multiband signals; multiband structure; spatial sampling patterns; spatial-domain signals; temporal sampling patterns; time indices; time-domain signals; Adaptive arrays; Arrays; Conferences; Correlation; Indexes; Sensors; Time-domain analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2013 IEEE 5th International Workshop on
  • Conference_Location
    St. Martin
  • Print_ISBN
    978-1-4673-3144-9
  • Type

    conf

  • DOI
    10.1109/CAMSAP.2013.6714102
  • Filename
    6714102