• DocumentCode
    739143
  • Title

    Improved trilinear decomposition-based method for angle estimation in multiple-input multiple-output radar

  • Author

    Jianfeng Li ; Ming Zhou

  • Author_Institution
    Dept. of Inf. Eng., Nanjing Univ. of Aeronaut. & Astronaut., Nanjing, China
  • Volume
    7
  • Issue
    9
  • fYear
    2013
  • fDate
    12/1/2013 12:00:00 AM
  • Firstpage
    1019
  • Lastpage
    1026
  • Abstract
    The joint direction of departure and direction of arrival estimation in bistatic multiple-input multiple-output radar is considered and an algorithm for the joint estimation is proposed. Through unitary transformation, the transmit direction matrix is transformed to be real-valued, and through data expansion based on the structure of the Vandermonde-like matrix, the receive array is twice as long as that of the conventional method. Then the trilinear decomposition can be used to obtain the estimations of the expanded receive direction matrix and real-valued transmit direction matrix, which contain the angle information. Finally the angles can be jointly estimated by using normalisation and least squares. The proposed algorithm requires no spectral peak searching and can achieve automatically paired estimations of angles, and it has better angle estimation performance and can detect more targets than the conventional trilinear decomposition-based method. Simulation results verify the performance of the proposed algorithm.
  • Keywords
    MIMO radar; direction-of-arrival estimation; least squares approximations; matrix algebra; Vandermonde-like matrix; angle estimation; angle information; automatically paired estimations; bistatic multiple-input multiple-output radar; data expansion; direction of arrival estimation; expanded receive direction matrix; improved trilinear decomposition-based method; least squares; real-valued transmit direction matrix; receive array; trilinear decomposition-based method; unitary transformation;
  • fLanguage
    English
  • Journal_Title
    Radar, Sonar & Navigation, IET
  • Publisher
    iet
  • ISSN
    1751-8784
  • Type

    jour

  • DOI
    10.1049/iet-rsn.2012.0345
  • Filename
    6684270