Persistent point scatterer statistical analysis for X-band SAR data: the Cosmo-SkyMed case study

This article addresses the problem of characterizing the statistical properties of persistent point scatterers (PPSs) retrieved in a stack of interferometric synthetic aperture radar (SAR) images. The set of parameters are exploited to obtain information about the radiometric response to microwave excitation and to infer some properties related to the physical nature of the targets.The permanent scatterers (PSs) technique is a well-known and worthwhile tool in the field of SAR interferometry and is used to detect terrain deformation with millimetrical accuracy. Although PSs have been adopted in many applications, the physical nature of these targets is still a matter of investigation. A good knowledge of the target properties, such as shape, size, orientation, and roughness, can be a key step for the correct interpretation of the terrain deformation mechanisms and for object identification.PPSs emerge as a subset of PSs that are characterized by a more stringent property; they have an impulsive trend both along and across track directions and sufficient isolation from other strong scatterers. These targets deserve particular attention, since few of them are able, for example, to provide high-precision antenna pattern shape and pointing estimation as well as accurate terrain deformation along the temporal baseline. In this work, the PPS intensity, signal-to-noise ratio (SNR), amplitude dispersion index, and antenna similarity index (a newly defined parameter) are statistically characterized for different kinds of land cover.A stack of images from the Cosmo-SkyMed constellation of satellites are exploited to obtain results for the PPS statistics on four different area typologies: full urban, suburban, vegetated and sparse buildings, and mountains with possible forested areas.