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.
Adaptive Detection of Rician Targets
IEEE Transactions on Aerospace and Electronic Systems ; 59 , 4 ; 4700-4708
2023-08-01
2111915 byte
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Pade approximations to Rician statistical functions
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|CORRESPONDENCE - Padé Approximations to Rician Statistical Functions
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