• DocumentCode
    177779
  • Title

    Off-the-grid spectral compressed sensing with prior information

  • Author

    Mishra, Kumar Vijay ; Myung Cho ; Kruger, A. ; Weiyu Xu

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Iowa, Iowa City, IA, USA
  • fYear
    2014
  • fDate
    4-9 May 2014
  • Firstpage
    1010
  • Lastpage
    1014
  • Abstract
    Recent research in off-the-grid compressed sensing (CS) has demonstrated that, under certain conditions, one can successfully recover a spectrally sparse signal from a few time-domain samples even though the dictionary is continuous. In this paper, we extend off-the-grid CS to applications where some prior information about spectrally sparse signal is known. We specifically consider cases where a few contributing frequencies or poles, but not their amplitudes or phases, are known a priori. Our results show that equipping off-the-grid CS with the known-poles algorithm can increase the probability of recovering all the frequency components.
  • Keywords
    compressed sensing; dictionaries; probability; signal sampling; time-domain analysis; CS; dictionary; known-pole algorithm; off-the-grid spectral compressed sensing; probability; spectrally sparse signal recovery; time-domain sampling; Atomic clocks; Compressed sensing; Dictionaries; Estimation; Indexes; Minimization; Signal resolution; basis mismatch; compressed sensing; known poles; matrix completion; spectral estimation;
  • 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.2014.6853749
  • Filename
    6853749