Bayesian Optimum Radar Detector Performances Against Ground Clutter Data
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چکیده
In this paper detection performances of the Bayesian Optimum Radar Detector (BORD) against nonGaussian ground clutter data are showed in the case of an unknown complex amplitude target. Recalling first how BORD was derived from the non-Gaussian SIRP model (Spherically Invariant Random Process) clutter we derive theoretical performances of the asymptotical expression of BORD which is CFAR with respect to the texture PDF of the SIRV. Then we compare BORD performances obtained in non-Gaussian ground clutter data with those of well-known optimum radar detectors such as Optimum KDetector (OKD) and Optimum Gaussian Detector (OGD).
منابع مشابه
BORD: bayesian optimum radar detector
We derive the expression of an optimum non-Gaussian radar detector from the non-Gaussian spherically invariant random process (SIRP) clutter model and a bayesian estimator of the SIRP characteristic density. SIRP modelizes non-Gaussian process as a complex Gaussian process whose variance, the so-called texture, is itself a positive random variable (r.v.). After performing a bayesian estimation ...
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تاریخ انتشار 2004