MMW radar scattering statistics of terrain at near grazing incidence

Abstract

The statistical behavior of clutter observed near grazing incidence and at 95 GHz is investigated for the specific cases of bare ground, snow-cover, and for a heterogeneous scene. The bare ground constitutes a homogeneous target under homogeneous conditions and the magnitude of the amplitude is Rayleigh distributed. While the snow-cover is a homogeneous target, the conditions under which it was observed are heterogeneous, and the Bayes rule is employed to describe its clutter distribution. The Bayes rule integrates variations due to signal fading with the underlying variations in the backscattering coefficient associated with the heterogeneity. The heterogeneous scene is also successfully described with the Bayes rule.

Application of frequency correlation function to radar target detection

“…In each realization, both the locations of the point target and the clutter response are randomly assigned. In recent studies [8,9], it was demonstrated that at near grazing incidence the MMW radar backscatter response of statistically homogeneous clutter complies with the Rayleigh statistical model. In other words, the phase of the scattered field is uniformly distributed and its power obeys an exponential probability density function (completely defined by its mean value).…”

Full-wave Characterization of Rough Terrain Surface Effects for Forward-looking Radar Applications: A Scattering and Imaging Study from the Electromagnetic Perspective

“…Once the image clutter distribution is known and an acceptable false-alarm rate chosen, a threshold value for the detectability of a target of a given RCS can be determined. For a statistically homogeneous terrain scene, in the absence of multipath and shadowing effects, the scattered field response (i.e., equivalently, the amplitude of the scattering matrix elements, |S pq |, or radar voltage response) is commonly found to conform to Rayleigh statistics (58). In other words, the real and imaginary parts of S pq are observed to be uncorrelated zero-mean Gaussian random variables with equal variances.…”

Comparison of GLR and invariant detectors under structured clutter covariance

“…It is common to model a complex valued radar image as linear in the target with additive Gaussian distributed clutter. Examples where a Gaussian model is justified for terrain clutter can be found in [17]. Even in cases when such a model is not applicable to the raw data, a whitening and local averaging technique can be implemented to obtain a Gaussian approximation [13].…”

“…Similarly to (16), the same scaling factor captures the common amplitude in both regions. With the partition in (13), the maximal invariant [7] under the group of transformations in (23) is composed of and in (17), and…”