• DocumentCode
    519583
  • Title

    Direction of arrival estimation based on smooth support vector regression

  • Author

    Xiang, He ; Bin, Jiang ; Jingli, Zhong ; Yueguang, Sun ; Liu, Zemin

  • Author_Institution
    Commun. Commanding Acad., Wuhan, China
  • Volume
    1
  • fYear
    2010
  • fDate
    21-24 May 2010
  • Abstract
    In this paper, we propose a new approach on direction of arrival (DOA) estimation based on smooth support vector regression. The proposed method can achieve higher accurate estimates for DOA while avoiding the all-direction peak value searching technique used in other traditional DOA estimation methods. Meanwhile, this approach reduces the extensive computations required by conventional super resolution algorithms such as MUSIC and is easier to implement in real-time applications. The proposed method map among the outputs of the array and the DOAs by means of a family of support vector machines. Computer simulation results show the effectiveness of the proposed method.
  • Keywords
    antenna arrays; antenna theory; array signal processing; direction-of-arrival estimation; regression analysis; support vector machines; vectors; DOA; MUSIC; all-direction peak value searching technique; direction of arrival estimation; smooth support vector regression; support vector machines; Constraint optimization; Convergence; Direction of arrival estimation; Helium; Machine learning; Multiple signal classification; Neural networks; Smoothing methods; Sun; Support vector machines; Direction of Arrival(DOA) estimation; Support Vector Machine(SVM); smooth support vector regression(SSVR);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Future Computer and Communication (ICFCC), 2010 2nd International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-5821-9
  • Type

    conf

  • DOI
    10.1109/ICFCC.2010.5497314
  • Filename
    5497314