On a SIRV-CFAR detector with radar experimentations in impulsive noise

This paper deals with radar detection in impulsive noise. Its aim is twofold. Firstly, assuming a Spherically Invariant Random Vectors (SIRV) modelling for the noise, the corresponding unknown covariance matrix is estimated by a recently introduced algorithm [1, 2]. A statistical analysis (bias, consistency, asymptotic distribution) of this estimate will be summarized allowing us to give the GLRT properties: the SIRV-CFAR (Constant False Alarm Rate) property, i.e. texture-CFAR and Covariance Matrix-CFAR, and the relationship between the Probability of False Alarm (PFA) and the detection threshold. Secondly, one of the main contributions of this paper is to give some results obtained with real non-Gaussian data. These results demonstrate the interest of the proposed detection scheme, and show an excellent correspondence between experimental and theoretical false alarm rates.