IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/6163529.html
   My bibliography  Save this article

Single Snapshot DOA Estimation by Minimizing the Fraction Function in Sparse Recovery

Author

Listed:
  • Changlong Wang
  • Jibin Che
  • Feng Zhou
  • Jinyong Hou
  • Chen Li

Abstract

Sparse recovery is one of the most important methods for single snapshot DOA estimation. Due to fact that the original - minimization problem is a NP-hard problem, we design a new alternative fraction function to solve DOA estimation problem. First, we discuss the theoretical guarantee about the new alternative model for solving DOA estimation problem. The equivalence between the alternative model and the original model is proved. Second, we present the optimal property about this new model and a fixed point algorithm with convergence conclusion are given. Finally, some simulation experiments are provided to demonstrate the effectiveness of the new algorithm compared with the classic sparse recovery method.

Suggested Citation

  • Changlong Wang & Jibin Che & Feng Zhou & Jinyong Hou & Chen Li, 2020. "Single Snapshot DOA Estimation by Minimizing the Fraction Function in Sparse Recovery," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-8, August.
  • Handle: RePEc:hin:jnlmpe:6163529
    DOI: 10.1155/2020/6163529
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2020/6163529.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/MPE/2020/6163529.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2020/6163529?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:jnlmpe:6163529. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.