• DocumentCode
    3102627
  • Title

    Spectral and sensor array analysis using maximum entropy with new eigenstructure constraints

  • Author

    Kirlin, R. Lynn

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Victoria Univ., BC, Canada
  • fYear
    1988
  • fDate
    3-5 Aug 1988
  • Firstpage
    146
  • Lastpage
    151
  • Abstract
    A number of modern spectral estimators are shown to have a common generic formulation. These include minimum variance, MUSIC, maximum entropy, and their enhanced versions. A new maximum entropy spectral estimator is derived using constraints on the modal powers or the expected-square projections of the data onto the eigenvectors of the data covariance matrix. It is conjectured that these constraints may be more suitable than those of conventional maximum entropy. A formulation is given that allows incorporation of uncertainty into the modal power constraints. The resulting estimators have quite reasonable forms, and similarities to previous estimators are discussed. It is noted that the new estimators allow further development when various a priori information can be incorporated into the constraints
  • Keywords
    eigenvalues and eigenfunctions; matrix algebra; spectral analysis; MUSIC; data covariance matrix; eigenstructure constraints; eigenvectors; expected-square projections; maximum entropy; minimum variance; modal powers; sensor array analysis; spectral array analysis; spectral estimators; Covariance matrix; Delay lines; Eigenvalues and eigenfunctions; Entropy; Multiple signal classification; Propagation delay; Sensor arrays; Signal analysis; Spectral analysis; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Spectrum Estimation and Modeling, 1988., Fourth Annual ASSP Workshop on
  • Conference_Location
    Minneapolis, MN
  • Type

    conf

  • DOI
    10.1109/SPECT.1988.206180
  • Filename
    206180