Compatibility Assessment of Multistatic/Polarimetric Clutter Data With the SIRP Model

Abstract

This article deals with the statistical inference of simultaneously recorded co-and cross-polarized bistatic coherent sea-clutter returns at S-band. This study is conducted employing appropriate statistical learning tools, involving the complex envelope of data, to assess the compliance of the available measurements with the spherically invariant random process (SIRP) representation, as well as to analyze possible texture correlations among the diverse polarimetric channels. Moreover, the spatial heterogeneity of the sea-clutter data is studied. The results highlight that the SIRP model is a good candidate for the representation of bistatic coherent clutter and usually the coherence time of the SIRP texture at the bistatic nodes is longer than that in the monostatic sensing. Notably, at bistatic angles in order of 60 • , the quadrature components of the cross-polarized bistatic measurements substantially exhibit a Gaussian behavior. These achievements further shed light on the bistatic sea-clutter diversity from the geometric and polarimetric point of view.

Statistical Parameters Extracted from Radar Sea Clutter Simulated under Different Operational Conditions

“…In [ 71 ], co-polarized and cross-polarized bistatic coherent sea-clutter returns were investigated with statistical inference. A spherically invariant random process (SIRP) was applied to describe the statistical properties of sea clutter, assuming a wide-sense stationary texture and speckle of sea clutter.…”

Testing Stationarity and Statistical Independence of Multistatic/Polarimetric Sea-Clutter With Application to NetRAD Data

“…requiring the joint characterization of the signals perceived at the different sensors. Due to the so called clutter diversity, the inference task becomes challenging since the statistical properties of the disturbance can change among the different nodes and polarizations [13]- [25]. In this respect, in [25] a statistical analysis of multistatic/polarimetric sea-clutter returns collected via the Netted RADar (NetRAD) system highlighted that, over an appropriate time interval (referred to as the coherence time), the sea-clutter returns collected from both monostatic and bistatic sensors can be modelled according to a Spherically Invariant Random Process (SIRP) [26]- [33].…”

“…Due to the so called clutter diversity, the inference task becomes challenging since the statistical properties of the disturbance can change among the different nodes and polarizations [13]- [25]. In this respect, in [25] a statistical analysis of multistatic/polarimetric sea-clutter returns collected via the Netted RADar (NetRAD) system highlighted that, over an appropriate time interval (referred to as the coherence time), the sea-clutter returns collected from both monostatic and bistatic sensors can be modelled according to a Spherically Invariant Random Process (SIRP) [26]- [33]. This is tantamount to describing the clutter backscattering over the coherence time as the product of a nonnegative random variable and a zeromean circularly symmetric Gaussian process with unknown spectral characteristics, referred to as texture and speckle, respectively.…”

“…This is tantamount to describing the clutter backscattering over the coherence time as the product of a nonnegative random variable and a zeromean circularly symmetric Gaussian process with unknown spectral characteristics, referred to as texture and speckle, respectively. However, the analyses performed in [25] relied on the use of uncorrelated slow-time samples and thus no inference on the possible stationarity of the speckle component was made. In this respect, this paper represents an important advancement of the study conducted in [25] accounting for possible correlations of the slow-time samples composing the observation vector 1 .…”

3D Localization for Multiplatform Radar Networks with Deployable Nodes

“…NetRAD, designed by the University College London and the University of Cape Town, is a low-cost, coherent, short-range (up to 1 km) pulse Doppler MPRN composed of three transmittingreceiving nodes operating over a 50 MHz bandwidth in Sband, and wire connected for time and phase control, as well as synchronization and data sharing. NetRAD was proved effective in detecting and localizing multiple moving targets, with a valuable performance boost as compared to monostatic and bistatic systems [23], leveraging clutter diversity [24]- [26]. NeXtRAD is a three nodes (one transmitting-receiving sensor, also acting as fusion centre, and two receiving units), dual band (X and L), fully polarimetric MPRN; the active node can transmit either horizontally or vertically polarized pulses in either X-or L-band and the receiving nodes can possibly acquire signals simultaneously on both polarizations [27].…”