We address the problem of detecting a signal of interest in Gaussian noise with an unknown covariance matrix, when the amplitude of the signal fluctuates along the observations and follows a Rice distribution. This is typical of a target that consists of one large dominant scatterer and a collection of small independent scatterers. We formulate it as a composite hypothesis testing problem, for which we derive the generalized likelihood ratio test, and show that it ensures a constant false alarm rate. Numerical simulations enable to assess its performance for Rician as well as Swerling I and III targets. It is shown that the new detector incurs no loss for Swerling targets but can offer a significant improvement for Rician targets, especially when the number of training samples is small.


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    Titel :

    Adaptive Detection of Rician Targets


    Beteiligte:


    Erscheinungsdatum :

    2023-08-01


    Format / Umfang :

    2111915 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch