Bayesian Optimum Radar Detector Performances Against Ground Clutter Data

Jean-Philippe Ovarlez (1) , Emmanuelle Jay (2) , Frédéric Pascal (3)

1 DEMR, ONERA, Université Paris Saclay (COmUE) [Palaiseau]
2 QAMLab
3 SONDRA - Sondra, CentraleSupélec, Université Paris-Saclay (COmUE)

In this paper detection performances of the Bayesian Optimum Radar Detector (BORD) against non-Gaussian 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 K-Detector (OKD) and Optimum Gaussian Detector (OGD).

Mots clés: Radar Detection; Non-Gaussian Clutter; SIRP

Domaines: Traitement du signal et de l'image [eess.SP]; Autres [stat.ML]; Applications [stat.AP]

Jean-Philippe Ovarlez, Emmanuelle Jay, Frédéric Pascal. Bayesian Optimum Radar Detector Performances Against Ground Clutter Data. Proc. of the IEEE-RADAR-04,, Oct 2004, Toulouse, France. ⟨hal-02495010⟩