This work describes the airborne Synthetic Aperture Radar (SAR) infrastructure developed at the Institute for Electromagnetic Sensing of the Environment (IREA) - National Research Council of Italy (CNR), Naples, Italy.The current infrastructure consists of a flight and a ground segment, including: a multi-frequency airborne SAR sensor operating at X- and L-band, owned by IREA-CNR; an IT platform for data storage and processing, located at the laboratories of IREA-CNR; an airborne SAR data processing chain, completely developed at IREA-CNR and University Parthenope, Naples, Italy.To show the current capabilities of this infrastructure in terms of characteristics of the final products as well as of quick response in emergency cases, a real world application scenario, namely, the monitoring of the volcanic area of Stromboli, Italy, in the frame of an agreement between IREA-CNR and the Department of Civil Protection of the Italian Presidency of the Council of Ministers, is presented.The short-term future perspectives related to the exploitation of this airborne SAR infrastructure are finally drawn, according to ongoing strengthening actions supported by already assigned fundings.

In this work we focus on the estimation of the soil permittivity from L-band polarimetric Synthetic Aperture Radar (SAR) data. To this aim, we consider SAOCOM-1 data collected in December 2021, over the province of La Pampa, in Argentina. The soil permittivity estimates, obtained through the Polarimetric Two-Scale Model (PTSM), are compared with the in-situ measurements collected at the same time of the SAR acquisition. Our results of the dielectric constant retrieved for the full scene are in accordance with a semi-arid landscape where the mode of the retrieved estimates is around εr~4 and a 2.41% relative error was found for ground data.

The problem of the identification of Radio Frequency Interferences (RFI) that corrupt Synthetic Aperture Radar (SAR) data is addressed in this work.In particular, we propose a new approach based on the minimization of the Bayesian Information Criterion (BIC) able to detect, on a pixel-by-pixel basis, the RFI signals within the considered SAR data.The performance of the proposed approach is assessed by means of both simulated and real-world airborne L-band SAR data corrupted by RFI signals.

The retrieval of the topographic changes induced by the eruptive activity of the Stromboli volcano, located in the Tyrrhenian Sea off Sicily (Italy), is the main topic of this contribution. In particular, we focus on the Stromboli activity during the July 2019 - October 2022 time period that was characterized by two violent explosions and months of lava emission inducing topography changes. These variations have been measured through the comparison of the generated airborne single-pass interferometric Synthetic Aperture Radar Digital Elevation Models.

We investigate in this work the soil moisture retrieval from P-band polarimetric Synthetic Aperture Radar (SAR) data. In particular, the analyzed SAR data were collected during a helicopter-borne campaign conducted over the Apulian Tavoliere plain, Southern Italy, on July 2021. The soil moisture estimates, obtained through the Polarimetric Two-Scale Model (PTSM), are then synthetically compared with in-situ measurements collected at the same time of the radar survey.

It is widely recognized that SAR images can suffer from the presence of RFI, especially at the low frequencies of the microwave spectrum. Such nuisance signals can significantly impair the quality of the SAR data with unwanted effects on the final products. This paper describes a processing strategy for the detection and cancellation of RFI signals corrupting airborne SAR raw-data. In addition, the performance of the proposed strategy is assessed by exploiting airborne L-band FMCW-SAR data.

Airborne synthetic aperture radar (SAR) data focusing in presence of highly variable squint angles is addressed in this work. To do this, a time-domain SAR focusing algorithm has been developed to account for the target-dependent nature of the acquisition squint angle. For comparison purposes, we have considered also a SAR processor based on the use of an azimuth-invariant processing squint angle. Moreover, real data acquired by two different X-band airborne SAR systems have been analyzed. The aims of the work are twofold. First, we show that the adoption of an azimuth-invariant processing squint angle, typically pursued by computationally efficient focusing strategies, may become inappropriate in several airborne missions, which are typically corrupted by motion errors induced by atmospheric turbulence. On the contrary, these problems are circumvented through the developed time-domain focusing strategy, which exploits a target-dependent processing squint angle that is coincident with the acquisition one. Second, we show that the proposed focusing strategy must be properly revised in the case of interferometric processing. In particular, we show that if the (target-dependent) acquisition squint angle is different for the two interferometric channels used, we have to move toward a different focusing paradigm, say, an interferometric focusing solution. This is again based on considering a target-dependent processing squint angle, but for each target, this processing angle should be equal neither to the acquisition squint angle of the “master” acquisition nor to that of the “slave” one: it must instead lie halfway between them. We prove that this approach is appropriate to obtain high interferometric coherence, and it is sub-optimal to separately focus the interferometric channels.

In recent years, airborne Synthetic Aperture Radar (SAR) remote sensing is becoming more and more attractive, thanks to the operational flexibility and observation capabilities provided by aerial SAR systems, and also due to the comparatively low-cost of these radar devices. In this work, we show the preliminary results relevant to the first acquisition campaign of the new Italian airborne Multiband Interferometric and Polarimetric SAR (MIPS) system, which is based on the Frequency Modulated Continuous Wave (FMCW) technology, and is able to operate at both X- and L-band.

In recent years, airborne Synthetic Aperture Radar (SAR) systems based on the Frequency Modulated Continuous Wave (FMCW) technology are becoming very popular thanks to their simple architecture and low cost. When FMCW SAR data are processed, it is essential to accurately know the electronic parameters of the system. In particular, the use of an incorrect value of the Frequency Sweep Rate (FSR) introduces geometric distortions in the focused images. In this work we provide the assessment of the performances of the FSRETC algorithm, recently proposed with the aim of estimating the correct FSR from the radar data. The presented analysis is conducted through the use of real data acquired by an airborne FMCW SAR system.

In this work, a time-domain procedure is presented to focus airborne Synthetic Aperture Radar (SAR) data collected in the presence of strong variations of the squint angle during the radar acquisition. The approach is tested on two datasets acquired by two different X-band airborne SAR systems.

In this work, we present some results of the flight-test campaign carried out with the AXIS system, which is an Italian single-pass interferometric airborne X-Band Synthetic Aperture Radar (SAR) based on the frequency modulated continuous wave technology. The system has recently been developed in the frame of a cooperation between a public research institute (IREA-CNR) and a private company (Elettra Microwave). The campaign was performed in 2018 over the Salerno area, South of Italy, and some corner reflectors (CRs) were deployed over the illuminated area with the aim of verifying the system performances in terms of geometric resolution and target location.

The retrieval of soil moisture and surface roughness from P-Band Synthetic Aperture Radar (SAR) data is here addressed. In particular, the presented methodology is based on the Polarimetric Two Scale Model (PTSM) recently proposed in the literature, and exploits the combination of SAR data collected along two antiparallel flight-tracks flown on the same area with a very short revisit time. Some considerations about the effects of the SAR acquisition geometry on the retrieval results are also provided. The used dataset is relevant to a desert campaign carried out in 2018 with the helicopter-borne P-band SAR system owned by the Italian Space Agency.

The Italian Space Agency (ASI) has recently entrusted CO.RI.S.T.A. with the development of a radar system that can be mounted onboard small airplanes or helicopters and may operate, at different frequencies belonging to the P-Band, either as Synthetic Aperture Radar (SAR) or as Sounder. In this work, we present preliminary results of the helicopter-borne desert campaign carried out with this system in 2018 over the Erfoud area, Morocco, in the frame of a project that has involved different public Italian Research Institutes and Universities.

This paper shows the design parameters and specifications of the AXIS system, which is an Italian single-pass interferometric airborne X-Band Synthetic Aperture Radar (SAR) based on the frequency modulated continuous wave technology. The activity is framed within a cooperation agreement signed between Elettra Microwave S.r.l and the Institute for Electromagnetic Sensing of the Environment (IREA) of the Italian National Research Council (CNR).

In this paper we derive a simple model to describe the distortions on focused airborne SAR data rising from the usage of inaccurate external information of the topography of the illuminated area. The model is based on the assumption that an accurate time-domain strategy is applied to focus the data. Moreover, perfect knowledge of the aircraft trajectory is also assumed, in order to better highlight the relation between true topography and airborne SAR focused data. The presented model takes into account the coupling between the trajectory deviations affecting the aircraft flight track and the topography errors. A closed form expression for both the amplitude and phase distortions corrupting the focused signal is provided. To validate the presented analysis some simulation results relevant to a realistic SAR acquisition scenario are finally shown.

The paper presents the results of an experiment carried out with a hybrid along-track (AT) / across-track (XT) interferometric Synthetic Aperture Radar (SAR) configuration in order to simultaneously estimating the velocity and the elevation pattern of the illuminated sea surface. In particular, the experiment has been carried out in 2013 with the X-band InSAeS4 airborne SAR system, which is equipped with three antennas installed in such a way to allow the simultaneous presence of three AT baselines and three XT baselines. The test-site is the coastline stretch of the Campania region, in the South of Italy, close to the Volturno river.

Recently, we have proposed a retrieval technique based on an original polarimetric two-scale model (PTSM), which is able to estimate the volumetric water content of bare soils from polarimetric synthetic aperture radar (SAR) data. In this paper, to extend the field of application of our retrieval technique to moderately vegetated soils, we combine the PTSM with a randomly oriented dipole-cloud volumetric scattering model, thus obtaining a polarimetric two-scale two-component model (PTSTCM). By using this model we show that, in principle, suitable combinations of the polarimetric SAR channels, i.e., “modified copolarized ratio” and “modified copolarized correlation coefficient,” are related only to the surface parameters because the dependence on the unknown volumetric contribution intensity cancels out. This allows us to retrieve soil moisture from L-band SAR data not only for bare soils but also in moderately vegetated areas, interested by a nonnegligible volumetric scattering contribution, provided that the double-bounce scattering component is negligible. In addition, describing the surface component by using the PTSM allows us to mitigate the well-known problem of overestimating the volume component, which affects most model-based target decompositions and that may lead to the so-called “negative power problem.” Both the performance and validity limits of the estimation method are assessed by comparing the obtained soil-moisture retrieval results to “in situ” measurements. To this aim, data from SMEX'03 and AGRISAR'06 campaigns available in literature are considered. They refer to sites with a flat topography. In particular, we employ the AGRISAR database, which includes data from several fields covering a period that spans all the phases of vegetation growth, to explore the validity range of the method in terms of vegetation height. Results of PTSTCM are also compared with those of available three-component methods (3CMs) employing more simplified surface scattering models. It has turned out that the use of the PTSTCM provides more accurate results for low vegetation (average modulus of soil moisture relative error for vegetation height smaller than 50 cm: 18.5% for the PTSTCM and 34% for the 3CM). Conversely, for higher vegetation, 3CMs should be more conveniently employed (average modulus of relative error for vegetation height greater than 50 cm: 17.5% for the 3CM and about 100% for the PTSTCM). A simple method to adaptively and automatically (i.e., based on measured data) select between PTSTCM and 3CM on a pixel-by-pixel basis is finally suggested, leading to a less than 20% average modulus of relative error on the retrieved soil moisture for the considered fields over the entire vegetation growth cycle.

The aim of this work is to show how an X-band radar system was able to instantly observe a phenomenon known as coastal upwelling. In fact, an X-band radar system is able to provide information about direction and intensity of the sea surface currents and waves in an area up to 3 nautical miles from the radar site. This capability, together with their flexibility and low cost, makes these devices useful tools for coastal monitoring and for the study of local small-scale phenomena as, for example, the upwelling. This phenomenon is, as generally recognized, the upward motion of deeper water while the surface ones are transported offshore by the stress of the wind blowing on the sea. Upwelled water is colder than surface water, moreover it is richer in nutrients and, as a consequence, it generates an increase in phytoplankton production (which in turn is able to boost food availability for fish populations) in the area affected by the upwelling. The characteristics of this phenomenon makes the X-band radar devices useful tools to support inshore fisheries, by monitoring environmental conditions at sea.

X-band marine radar systems represent a flexible and low-cost tool for the tracking of multiple targets in a given region of interest. Although suffering several sources of interference, e.g., the sea clutter, these systems can provide high-resolution measurements, both in space and time. Such features offer the opportunity to get accurate information not only about the target position/motion but also about the targets size. Accordingly, in this paper, we exploit emergent extended target tracking (ETT) methodologies in which the target state, typically position/velocity/acceleration, is augmented with the target length and width. In this paper, we propose an ETT procedure based on the popular probability hypothesis density filter, and in particular, we describe the extended target state through the gamma Gaussian inverse Wishart model. The comparative simplicity of the used models allows us to meet the real-time processing constraint required for the practical surveillance purposes. Real-world data from an experimental and operational campaign, collected during the recovery operations of the Costa Concordia wreckage in October 2013, are used to assess the performance of the proposed target tracking methodology. The full signal processing chain is implemented, and considerations of the experimental results are provided. Important nonideal effects, common to every marine radar, are observed and discussed in relation to the assumptions made for the tracking procedure.

In this paper we introduce an algorithm to retrieve the soil moisture content and the surface roughness of a moderately vegetated soil from a fully polarimetric SAR dataset. The estimation procedure is founded on the prediction of the second order statistics of the scattered field provided by the Polarimetric Two-Scale Model combined with a two-component scattering model. The performance of the estimation algorithm is assessed by comparing obtained retrieval results to “in situ” measurements. To this aim, data from Little Washita SMEX'03 campaign available in literature are employed.

This work deals with the analysis of a novel data processing approach to estimate the local depth in a shallow coastal area starting from X-band radar data. The approach is based on the maximization of the Normalized Scalar Product (NSP) between the measured and the theoretical wave dispersion relations, which embed the dependence on the searched for parameters (current vector and depth). In the present work, we presented an improvement version of NSP approach able to estimate the local depth, which allows to obtain a high resolution spatial map (subpixel) of the investigated area. The performances of the NSP approach is evaluated by comparing the estimated bathymetry with the ground truth provided the multi-beam echo sounder reported on the same grid resolution of the bathymetric maps of the X-band radar images.

REMOCEAN is a remote sensing system for the wave and current monitoring, based on a nautical X-Band radar, usually deployed for navigation and ship traffic control. Here, we present the results obtained by the analysis of the data collected by the Remocean system, installed in the port of Giglio Island, during the storm of the 27 November 2012. For this test case, the effectiveness of the Remocean wave height reconstruction has been evaluated by analyzing the spectral slope and the statistical properties of the ocean waves and comparing them with independent measures provided by a buoy installed in the proximity the `Costa Concordia' shipwreck.

New Synthetic Aperture Radar (SAR) missions in S-band are currently under design but the potential performance of this microwave frequency is still under discussion. This paper presents the outcomes of a study on canopy classification carried out with fully polarimetric S- and X-band datasets contemporaneously acquired by the Astrium airborne SAR demonstrator. Classical polarimetric decompositions have been applied to investigate the S-band capabilities in vegetation monitoring and preliminary results are here presented.

Electromagnetic models for surface scattering represent a handy analytical tool useful in many remote sensing applications which exploit the prediction of the scattered field. Of course, the better is the surface model employed to compute the electromagnetic scattering, the more accurate are the forecasts on the scattered field, provided that closed form solutions for the statistics of the field are attainable. Accordingly, it is widely recognized that statistical scale-invariance properties exhibited by natural surfaces within a wide observation scale range are very efficiently described by means of fractal geometry. In this paper we focus on the Kirchhoff solution for the scattering from both classical and fractal surfaces, so allowing us to provide a novel physical interpretation of the Kirchhoff scattering integral in terms of the probability density function of the slopes of an equivalent rough surface.

In this paper we present the results of a project approved in the frame of the 2007 Cosmo-Skymed AO, devoted to use high resolution data for hydrology applications in semi-arid context. A case study was developed in Burkina Faso, a West Africa country, characterized by the alternation of intense rainy and dry seasons. In this paper we present the rationale of the project along with two of the obtained products concerning the estimation of eroded areas and the surface water recharge.

An algorithm able to retrieve the soil moisture content and the surface roughness of a bare soil from a set of measured HH-, VV-SAR images is here presented. The estimation procedure is founded on the prediction of power densities and correlation between the copolar channels provided by the Polarimetric Two-Scale Model that we recently proposed. The performance of the estimation algorithm is assessed by comparing obtained retrieval results to “in situ” measurements. To this aim, data from Little Washita SMEX'03 campaign available in literature are employed.

This paper presents the main scientific novel outcomes of the research activities included in the project “Buildings Feature Extraction from Single SAR Images: Application to COSMO-SkyMed High Resolution SAR Images”. The project was conceived by the authors of this paper and financed by the Italian Space Agency under the Announcement of Opportunity for the COSMO/SkyMed mission.

We propose a polarimetric two-scale surface scattering model employed to retrieve the surface parameters of bare soils from polarimetric synthetic aperture radar or scatterometer data. The scattering surface considered here is composed of slightly rough randomly tilted facets, for which the small perturbation scattering method holds. The facet random tilt causes both a random variation of the local incidence angle and a random rotation of the local incidence plane around the line of sight. Unlike other similar already existing approaches, our method considers both these stochastic effects in the analytical evaluation of the facet scattering matrix, and their statistical modeling is derived from a proper statistical description of the scattering surface. In particular, we assume that the facet slope (i.e., the slope of the large-scale surface roughness) is a Gaussian random variable, in agreement with both classical and fractal surface models. The proposed scattering model is then used to retrieve bare soil moisture and (large-scale) roughness from the co- and cross-polarized ratios. The performance of the resulting retrieval algorithm and its validity limits are finally assessed by comparing obtained results to “ in situ” measurements. To this aim, data from different measurement campaigns available in literature are employed.

A polarimetric two-scale surface scattering model employed to retrieve the surface parameters of bare soils from polarimetric SAR data is proposed. The scattering surface is considered as composed of slightly rough randomly tilted facets, for which the Small Perturbation Method holds. The facet random tilt causes a random variation of the local incidence angle, and a random rotation of the local incidence plane around the line of sight, which in turn causes a random rotation of the facet scattering matrix. Unlike other similar already existing approaches, our method considers both these effects. The proposed scattering model is then used to retrieve bare soil moisture and (large-scale) roughness from the co-polarized and cross-polarized ratios. The performances of the resulting retrieval algorithm is finally assessed by comparing obtained results to “in situ” measurements. To this aim, data from Little Washita campaign available in literature is employed.

In this paper we introduce an original formulation for the electromagnetic field diffraction by a knife edge with random roughness: the formulation, based on the Asymptotic Physical Optics (APO) approach, leads to closed form evaluations of the statistics of the diffracted field. A very interesting conclusion is that, for moderate edge roughness, the diffracted field propagation can be described in terms of the same ray congruence as in the straight (smooth) edge case, with the only difference that the field associated to each ray is a random variable whose statistics are, in this paper, computed in closed form. The presented approach can be then considered as a first step toward a general Stochastic Theory of Edge Diffraction (STED).