• DocumentCode
    1538267
  • Title

    The CFAR adaptive subspace detector is a scale-invariant GLRT

  • Author

    Kraut, Shawn ; Scharf, Louis L.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Colorado Univ., Boulder, CO, USA
  • Volume
    47
  • Issue
    9
  • fYear
    1999
  • fDate
    9/1/1999 12:00:00 AM
  • Firstpage
    2538
  • Lastpage
    2541
  • Abstract
    The constant false alarm rate (CFAR) matched subspace detector (CFAR MSD) is the uniformly most-powerful-invariant test and the generalized likelihood ratio test (GLRT) for detecting a target signal in noise whose covariance structure is known but whose level is unknown. Previously, the CFAR adaptive subspace detector (CFAR ASD), or adaptive coherence estimator (ACE), was proposed for detecting a target signal in noise whose covariance structure and level are both unknown and whose covariance structure is estimated with a sample covariance matrix based on training data. We show here that the CFAR ASD is GLRT when the test measurement is not constrained to have the same noise level as the training data, As a consequence, this GLRT is invariant to a more general scaling condition on the test and training data than the well-known GLRT of Kelly (1986)
  • Keywords
    adaptive estimation; adaptive signal detection; matched filters; maximum likelihood detection; noise; CFAR MSD; CFAR adaptive subspace detector; adaptive coherence estimator; constant false alarm rate matched subspace detector; covariance matrix; covariance structure; generalized likelihood ratio test; scale-invariant GLRT; scaling condition; target signal; uniformly most-powerful-invariant test; Adaptive signal detection; Covariance matrix; Detectors; Noise level; Noise measurement; Signal detection; Signal to noise ratio; Testing; Training data; Variable speed drives;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/78.782198
  • Filename
    782198