• DocumentCode
    3429800
  • Title

    Hybrid Cramér-Rao bound for joint estimation of target and ionospheric parameters using MIMO-OTH radar

  • Author

    Mao Li ; Qian He ; Zishu He ; Blum, Rick S.

  • Author_Institution
    EE Dept., Univ. of Electron. Sci. & Tech. of China, Chengdu, China
  • fYear
    2013
  • fDate
    6-10 July 2013
  • Firstpage
    6
  • Lastpage
    10
  • Abstract
    Exploiting the received signals, which are usually not employed in the traditional OTH radar for ionospheric parameter estimation, we study joint estimation of target and ionospheric parameters for multiple-input multiple-output skywave OTH (MIMO-OTH) radar. We employ a parabolic layer model to characterize the ionospheric distortions. We model the target and ionospheric parameters as deterministic and random unknowns, respectively, and carry out the joint estimation using a hybrid maximum likelihood and maximum a posterior (ML/MAP) method. The corresponding hybrid Cramér-Rao bound (HCRB) is derived. We show that the proposed joint estimation approach leads to an improved accuracy for the target and ionospheric parameter estimation compared with the traditional methods.
  • Keywords
    MIMO radar; maximum likelihood estimation; parameter estimation; HCRB; MIMO-OTH radar; ML-MAP method; deterministic unknowns; hybrid Cramér-Rao bound; hybrid maximum likelihood method; ionospheric distortions; ionospheric parameter estimation; joint estimation approach; maximum a posterior method; multiple-input multiple-output skywave OTH radar; parabolic layer model; random unknowns; target parameter estimation; Joints; MIMO; Manganese; Maximum likelihood estimation; Radar; Signal to noise ratio; Hybrid Cramér-Rao bound; MIMO-OTH radar; hybrid ML/MAP estimation; joint estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal and Information Processing (ChinaSIP), 2013 IEEE China Summit & International Conference on
  • Conference_Location
    Beijing
  • Type

    conf

  • DOI
    10.1109/ChinaSIP.2013.6625286
  • Filename
    6625286