Exploring Homogeneity and Covariance Matrix Structure of Multistatic/Polarimetric Sea-Clutter Data

The design of bespoke adaptive detection schemes relying on the joint use of multistatic/polarimetric measurements requires a preliminary statistical inference on the clutter interference environment. This is fundamental to develop an analytic model for the received signal samples, which is used to synthesize the radar detector. In this respect, the aim of this paper is the design of suitable learning tools to study some important statistical properties of the sea-clutter environment perceived at the nodes of a multistatic/polarimetric radar system. The study is complemented by the use of radar returns measured with the Netted RADar (NetRAD), which collects simultaneously monostatic and bistatic measurements. Precisely, the homogeneity properties of the data in the slow-time domain are first assessed resorting to Generalized Inner Product (GIP) based statistics. Then, the possible presence of structures in the clutter covariance matrices (both inter and intra channels) is investigated through ad-hoc statistical tools. The results show that the data, regardless the polarimetric/geometric configuration, can be modeled as drawn from a stationary process within the coherence time. Moreover, for both the monostatic and the bistatic returns the structure of the covariance matrix depends upon the polarimetric/geometric configuration of the sensing system.