• DocumentCode
    1059992
  • Title

    The Constrained CramÉr–Rao Bound From the Perspective of Fitting a Model

  • Author

    Moore, Terrence J. ; Kozick, Richard J. ; Sadler, Brian M.

  • Author_Institution
    Army Res. Lab., Adelphi
  • Volume
    14
  • Issue
    8
  • fYear
    2007
  • Firstpage
    564
  • Lastpage
    567
  • Abstract
    Stoica and Ng (1998) presented a simple expression for the constrained Cramer-Rao bound (CCRB) when the constraints are given by a differentiable function of the parameter to be estimated. This letter considers the parallel case in developing the CCRB when the parameters are locally fitted to a lower-dimensional parametric model, i.e., the parameters are locally assumed to be functions of a distinct reduced parameter vector. We employ classical elements of CRB theory on the locally fitted model to present a very simple derivation of the CCRB, conditions for attaining the bound, and a regularity condition. Examples illustrate the key ideas.
  • Keywords
    parameter estimation; statistical distributions; constrained Cramer-Rao bound; differentiable function; distinct reduced parameter vector; lower-dimensional parametric model; model fitting; parallel case; Covariance matrix; Laboratories; Lagrangian functions; Maximum likelihood estimation; Null space; Parameter estimation; Parametric statistics; Taylor series; Testing; Constrained CramÉr–Rao bound (CCRB); equality constraints; model fitting;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1070-9908
  • Type

    jour

  • DOI
    10.1109/LSP.2006.891316
  • Filename
    4276740