• DocumentCode
    239618
  • Title

    Multistatic radar imaging via decentralized and collaborative subspace pursuit

  • Author

    Gang Li ; Varshney, Pramod K. ; Zhang, Yimin D.

  • Author_Institution
    EE Dept., Tsinghua Univ. Beijing, Beijing, China
  • fYear
    2014
  • fDate
    20-23 Aug. 2014
  • Firstpage
    710
  • Lastpage
    714
  • Abstract
    The task of multistatic radar imaging can be converted to the problem of jointly sparse signal recovery. In this paper, the algorithm named decentralized and collaborative subspace pursuit (DCSP) is utilized in multistatic radar systems to obtain a high-resolution image. By embedding collaboration among radar nodes and fusion strategy into each iteration of the standard subspace pursuit (SP) algorithm, DCSP is capable of providing satisfactory image even if some radar nodes suffer from relatively low signal-to-noise ratios (SNRs). Compared to the existing algorithms based on linear programming, DCSP has much lower computational complexity at the cost of increased communication overhead in the radar network.
  • Keywords
    computational complexity; image fusion; image resolution; iterative methods; linear programming; radar imaging; radar resolution; DCSP; SNRs; SP algorithm; communication overhead; computational complexity; decentralized and collaborative subspace pursuit; fusion strategy; high-resolution image; jointly sparse signal recovery problem; linear programming; low signal-to-noise ratios; multistatic radar imaging system; radar network; radar nodes; standard subspace pursuit algorithm; Collaboration; Imaging; Multistatic radar; Radar imaging; Signal processing algorithms; Standards; Multistatic radar imaging; compressive sensing; subspace pursuit;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Digital Signal Processing (DSP), 2014 19th International Conference on
  • Conference_Location
    Hong Kong
  • Type

    conf

  • DOI
    10.1109/ICDSP.2014.6900756
  • Filename
    6900756