Hybrid compact polarimetric (CP) SAR systems present significant advantages with respect to fully polarimetric (FP) ones, in terms of hardware simplification and better attainable resolution and coverage. Retrieval of soil moisture is a classical application of FP SAR data: in this context, advanced model-based techniques have been proposed to support microwave data inversion. In this paper, we present a new approach for soil moisture retrieval from CP data, based on the use of the Polarimetric Two-Scale Model (PTSM), which has been originally proposed in support of soil moisture retrieval from FP data. Obtained results are validated using simulated CP data relevant to the AgriSAR campaign test sites and compared with FP PTSM-based retrieval results.

We here analytically evaluate the spatial correlation coefficient of an interferometric pair obtained by combining two bistatic SAR acquisitions. The scattering surface is described as randomly rough, and the Kirchhoff Approximation (KA) or the first-order Small Slope Approximation (SSA1) are used to compute scattered fields. Both approximations lead to the same expression of the correlation coefficient, that generalizes to the bistatic case, with arbitrary acquisition geometry, the result available in literature for usual monostatic SAR interferometry.

This paper is aimed at supporting the analysis and interpretation of bistatic synthetic aperture radar (SAR) images, which are available by now through the Capella constellation or will be soon available thanks to the upcoming PLATiNO-1 mission. More specifically, here we focus on urban areas, where the so-called cardinal effect dominates the backscattering in conventional monostatic SAR imagery. Such effect is also evident in bistatic acquisition geometries, as it has been recently demonstrated, even if with different dynamics. Through the application of analytical models for the electromagnetic scattering from buildings in bistatic geometries, we provide a physical explanation of the SAR image formation in the urban environment and in arbitrary acquisition geometries. We quantitatively evaluate the contrast between the returns from the building and the surrounding terrain under different roughness regimes and imaging geometries. The analyses provided here might support a correct human interpretation and automatic processing of urban bistatic SAR images.

Natural surfaces exhibit scale-invariance properties and power-law spectra over a wide range of scales. For this reason, they are well described in the frame of fractal geometry and, in particular, using fractional Brownian motion (fBm) two-dimensional statistical processes. In this paper, we present the derivation of the correlation of Global Navigation Satellite System reflectometry signals scattered by a fBm surface. We here show that this correlation depends on a parameter related to the root-mean-square surface slope as measured at the electromagnetic wavelength scale. When this parameter increases, the correlation smoothly decreases from a value close to unity reaching the value of the roughness-independent expression already available in the literature. In our experiments, based on roughness measurements available in the literature, we firstly show how the description of the roughness of natural surfaces can be conveniently obtained via fBm parameters. Then, we illustrate the behavior of the correlation time for different roughness regimes. For a high-altitude airborne receiver, values ranging from about 6 ms (as predicted by the expression already available in the literature) to several tens of milliseconds are obtained.

In the context of bistatic synthetic aperture radar (SAR) imaging, SAR interferometry is an appealing application due to the capability of retrieving accurate topographic information or surface deformations at fractions of wavelength. Within this framework, we present a new physical-based approach to evaluate the correlation between a pair of bistatic SAR acquisitions over a bare soil surface and in a very general imaging geometry, which includes two transmitters and two receivers. Some specific configurations of practical interest for proposed bistatic spaceborne SAR missions, for example, SESAME and PLATiNO-1 (PLT-1), namely coplanar and along-track bistatic geometries, are analyzed as well. The proposed methodology makes use of electromagnetic scattering models suited to random rough surfaces, namely the Kirchhoff approximation (KA) and the first-order small-slope approximation (SSA1), under which analytical formulations of the correlation between the received electromagnetic fields are derived. It is found that in the coplanar imaging geometry, a unitary correlation coefficient can be obtained with nonnull orthogonal baselines. Closed-form expressions of the critical baseline are derived as well. The proposed approach can be applied to such scenarios where single surface scattering is the dominant mechanism, such as bare soil surfaces or scarcely to moderately vegetated areas.

Models linking the electromagnetic field scattered from the sea surface along the specular direction to the speed of the wind blowing over the surface are of fundamental importance for wind speed retrieval via Global Navigation Satellite System Reflectometry (GNSS-R). In this work, by modelling the sea surface as a fractional Brownian motion (fBm) random process and using the Kirchhoff approximation (KA), we express the sea bistatic normalized radar cross section (NRCS) σ0at specular direction directly in terms of sea surface spectrum parameters, and hence of wind speed. This avoids the need of intermediately computing the large-scale sea surface slope variance, which in turn would require the definition of a somewhat arbitrary cut-off surface wavenumber. We show that the obtained theoretical relationship between wind speed and σ0is in reasonable agreement with the empirical ones available in literature.

Interpretation and processing of synthetic aperture radar (SAR) imagery is negatively affected by speckle noise, that can be faced by proper despeckling pre-processing. In this work, we propose a simple approach for the despeckling of multi-frequency SAR data under the hypotheses that they are relevant to bare soil surfaces and that are acquired by the same sensor, e.g., AIRSAR. The proposed approach is based on a frequency-compensation step, where the dependence of the signal strength upon operating frequency is compensated by means of surface scattering model suited to natural surfaces. Once such a pre-processing step is carried out, any despeckling filter suited to SAR time series filtering can be applied. Quantitative indicators evaluated on both simulated and actual SAR data reveal the benefits of the proposed compensation step w.r.t. pure multitemporal and single-channel filtering.

This research examines the application of Interferometric Synthetic Aperture Radar (InSAR) from space for tracking and evaluating surface and structural changes in transport networks, particularly a 65 km stretch of the A16 highway in Southern Italy. The project merges various elements like the design planimetry of the infrastructure, SAR image datasets, measurements taken on-site, and an updated Landslide Inventory Map (LIM) to validate the compatibility of SAR outcomes with conventional monitoring techniques, especially inclinometers. Considering the widespread presence of erosional and gravitational events, such as landslides in this area, effective surveillance is crucial. The investigation utilizes COSMO-SkyMed imagery from 2015-2022. These data are processed via the Coherence Pixels Technique (CPT) algorithm, delivering numerous Persistent Scatterers (PSs). Inclinometers were used to record ground deformations and authenticate DInSAR products, showing alignment between the two different methodologies. The research highlights the value of DInSAR measurements for overseeing infrastructural changes caused by geological occurrences like landslides. These data could be integrated into an early warning mechanism, supporting decision-making processes for managing transport networks.

Sea and soil surfaces exhibit power-law spectra over a wide range of spatial frequencies. An analytical formulation of the electromagnetic scattering from such surfaces can be obtained via the two-scale model (TSM). However, this approach requires the definition of a cutoff surface wavenumber, separating the low- and high-frequency parts of the surface spectrum. The final obtained normalized radar cross section (NRCS) value is dependent on the choice of this cutoff wavenumber, which is, to some extent, arbitrary. This problem can be avoided by describing power-law spectrum surfaces via the theory of fractional Brownian motion (fBm) two-dimensional (2-D) random processes. The bistatic NRCS of an fBm surface can be analytically evaluated by using the Kirchhoff approximation (KA) or the first-order small slope approximation (SSA-1): its expression is related to the probability density function (pdf) of an alpha-stable random process, and it can be efficiently evaluated by means of proper asymptotic series expansions. However, fBm surfaces are statistically isotropic, whereas natural surfaces are often anisotropic. Therefore, in this work, we first of all show that an anisotropic power-law spectrum surface can be considered as a generalized anisotropic fBm surface; then, we present an analytical formulation of its NRCS, based on SSA-1; and finally, we compare the obtained results with measured NRCSs of natural surfaces and with NRCS values obtained via more accurate but more computationally demanding methods that require the numerical evaluation of scattering integrals.

In the framework of passive multistatic radars, formation-flying synthetic aperture radar (FF-SAR) represents an intriguing remote sensing solution due to the enhanced imaging capabilities with respect to the conventional SAR. In this article, we focus on FF-SAR systems operating in a far-from-transmitter geometry, developing a signal model suited to this specific configuration. Additionally, we present an efficient processing scheme that, by properly combining the received raw echoes in a coherent fashion, enables two peculiar imaging modes of FF-SAR, namely, signal-to-noise ratio (SNR) improvement and high-resolution wide swath (HRWS). Simulation results show that achieved radiometric and geometric imaging performances are in line with those offered by an equivalent monostatic SAR. In HRWS imaging mode, azimuth ambiguity suppression and SNR improve as the number of satellites increases and are maximized by specific receivers along-track baselines, whose expression is provided. Finally, we present a statistical analysis of the processing performance parameters for random receivers’ positions, both assuming a fixed pulse repetition frequency (PRF) and allowing for an adaptive PRF tuning. This last analysis is also directly applicable to clusters of SAR receivers not far from the transmitter.

We present an analytical formulation of the correlation of the electromagnetic fields scattered by a rough or gently undulating surface and measured at two spatially separated points. The latter may be the positions of two different bistatic radar sensors receiving the scattered field at the same time, as in bistatic synthetic aperture radar interferometry, or two positions occupied by a single moving receiver at two slightly different times, as in Global Navigation Satellite System Reflectometry. The scattering surface is modeled as randomly rough, and the Kirchhoff Approximation is employed to compute the scattered field. The obtained closed-form expression of the field correlation is substantially coincident with the one already available in literature for far-from-specular scattering directions; conversely, for close-to-specular directions, the obtained formulation shows that, as the surface correlation length increases, the degree of coherence smoothly increases from the value obtained with the expression available in literature for rough surfaces to a value close to unity for very gently undulating surfaces.

We present an analytical formulation of the correlation coefficient of the electromagnetic fields scattered at near-specular direction by a rough or gently undulating surface and measured at two spatially separated positions occupied by a moving receiver at slightly different times. This allows us obtaining an explicit expression of the correlation time of the received signal in terms of radar and surface parameters. This work provides a contribution to the discussion, currently ongoing in the Global Navigation Satellite System Reflectometry (GNSS-R) scientific community, about the behavior of received signal fluctuations, especially when surface profile variations are such that the scattering is neither coherent nor completely incoherent. The scattering surface is here modeled as randomly rough, and the Kirchhoff Approximation (KA) or the first-order Small Slope Approximation (SSA1) is employed to compute the scattered field. In fact, the expression of the correlation coefficient is the same for both approximations. The obtained closed-form expression shows that, as the surface correlation length increases, the degree of coherence smoothly increases from the value obtained with the expression already available in literature for very rough surfaces to a value close to unity for gently undulating surfaces. The obtained behavior of correlation time as a function of surface parameters, system resolution and observation geometry is in agreement with numerical simulations available in literature. More in general, obtained analytical results are in agreement with the observed behavior of GNSS-R signals over flat land surfaces.

In this article, we propose a novel benchmarking framework for a quantitative assessment of the performance of despeckling algorithms for multitemporal synthetic aperture radar (SAR) imagery. A number of canonical scenes and data sets are analyzed so as to investigate both speckle reduction and feature preservation capabilities of the filters. Despeckling performance is evaluated by proper quality measures that are defined according to the scene. Due to the lack of real-world speckle-free SAR images, the proposed benchmarking tool relies on an accurate and well-assessed SAR simulator which allows for generating realistic SAR images accounting for electromagnetic (EM) and geometrical parameters of the sensed surface. Accuracy and convergence properties of filters are first measured on scenes with stationary reflectivity. Then, for a more realistic performance prediction in practical situations, the effects of temporal changes of the scene reflectivity on the despeckled images are measured on time series with time-varying reflectivity. In the latter case, performance parameters are intended to measure the capability of the filter to preserve both the perturbation and its impact on the other bands. The whole benchmarking framework is applied to a representative set of state-of-the-art multitemporal filters. Interestingly, their performance as evaluated by means of our framework is well in agreement with (qualitative) visual inspections by SAR specialists. Proposed quality metrics are measured under the hypothesis of uncorrelated bands, which defines the best case for most multitemporal filters. A numerical sensitivity analysis of the performance of filters against correlation coefficient is carried out to investigate the temporal correlation effects on the despeckled time series.

The paper focuses on the concept of a formation-flying synthetic aperture radar (FF-SAR) bistatic system composed of a set of compact, low-weight satellite receivers in close formation (within 1 km) placed in the same low-Earth orbit at large distance (about 100 km) from a transmitter. Each receiver is conceived to fit a 12-unit CubeSat. A signal model adapted to the proposed formation geometry is also presented, and a corresponding processing scheme to achieve range swath widening and signal-to-noise ratio (SNR) improvement is illustrated and discussed.

This paper discusses a new receiving antenna for remote sensing applications to be mounted onboard a formation-flying synthetic aperture radar (FF-SAR) bistatic system based on the CubeSat standard. The formation works as a bistatic SAR collecting microwave signals coming from a transmitting SAR unit. The receiving antenna has been designed according to the acquisition modes of the formation, namely a stripmap mode for signal-to-noise ratio improvement and a High-Resolution Wide-Swath mode for the monitoring of large regions. In order to meet the very different requirements for both operating modes with the physical constraints imposed by the nanosat geometry, a large reflector with reconfigurable feed has been conceived and simulated. The results show that the proposed antenna accomplishes the design specifications.

In this paper, we provide a link budget analysis of the Global Navigation Satellite System-Reflectometry (GNSS-R) signal scattered off the sea surface in arbitrary viewing geometries. The study is based on a recent electromagnetic scattering two-scale model for rough surfaces, named BA-PTSM, which is able to accurately describe the microwave scattering from sea surface at any acquisition geometry, including backscattering and forward-scattering, and on a simulator that accounts for geometrical and system parameters. Comparisons with Geometrical Optics (GO), whose validity is limited to specular and quasi-specular scattering, demonstrate that a reliable simulation of GNSS-R signals in configurations other than the conventional forward-scattering one calls for scattering models more accurate than GO, e.g., BA-PTSM.

Bistatic radars have been a topic of increasing interest in recent years, thanks to the introduction of new bistatic (and multistatic) configurations, including those based on the opportunistic exploitation of global navigation satellite systems (GNSSs). The research on bistatic electromagnetic scattering models plays an important role in the analysis of these systems, in their simulation, and in the prediction of their performance. The two-scale model (TSM) is a widely used approach for the computation of scattering from rough surfaces, since it is able to account for depolarization effects due to surface tilting. However, in its original formulation, it requires a computationally intensive numerical integration, in order to perform appropriate average over surface random slopes. To overcome this limitation, a closed-form polarimetric TSM (PTSM) was developed, which has been also recently extended to the case of anisotropic rough surfaces (A-PTSM), with a focus on the sea surface. The A-PTSM can be efficiently used to compute the backscattering from anisotropic rough surfaces and can support the development and analysis of monostatic radar missions. In order to extend its scope to the general case of bistatic and multistatic configurations, in this article, we extend the A-PTSM to the case of bistatic electromagnetic scattering, presenting the evaluation of all the elements of the bistatic polarimetric covariance matrix. Due to the relevance of circularly polarized signals in opportunistic GNSS reflectometry applications, both the linear and the circular polarization bases are considered. The behavior of the obtained elements is discussed, and simplified expressions of the elements of the covariance matrix are provided for the case of scattering within the incidence plane. Relevant numerical examples are provided and compared to those obtained by the more refined, but more computationally intensive, second-order small-slope approximation (SSA2) method. In the examples, we consider both a wind-driven sea surface and a tilled soil, and both L-band and X-band frequencies. However, the presented method can be used at all frequencies of interest for microwave remote sensing and for all observation geometries, except for near grazing incidence and/or scattering.

The Two-Scale Model (TSM) is a useful approach for the evaluation of scattering from rough surfaces. In order to model depolarization effects, TSM, in its original formulation, requires an average operation that calls for numerical integration, so strongly reducing the computation efficiency. However, in the last decade a method to analytically compute this average in closed form, named Polarimetric TSM (PTSM), was devised. More recently, the PTSM, originally applied to backscattering from statistically isotropic rough scattering surfaces, was extended to the case of anisotropic rough surfaces (A-PTSM), in order to compute backscattering from sea surfaces. Both PTSM and A-PTSM, as presented in previous work, only consider the monostatic configuration. Here, we extend A-PTSM to the more general case of bistatic scattering. In particular, we present the procedure to obtain all the elements of the bistatic polarimetric covariance matrix in closed form; we then present some numerical results with reference to the bistatic Normalized Radar Cross Sections (NRCS) in circular polarization basis, which are of interest for some recently proposed bistatic passive radar systems with GNSS signals of opportunity.

In this work we present a novel benchmarking framework for assessing the quality of despeckled multitemporal SAR images on an objective basis. Taking cues from a recent work providing a useful tool for measuring the performance of single-channel despeckling filters, here we extend that analysis to multitemporal filters and datasets. Due to the lack of reference speckle-free real SAR images, the quantitative performance parameters introduced here are evaluated on simulated time series of canonical scenes obtained through a reliable and well-assessed SAR simulator which accounts for both geometrical and electromagnetic properties of the scattering surface. First we analyze image quality over datasets with homogeneous reflectivity in time. Then, for a more realistic performance assessment in practical situations, ad-hoc quality parameters are introduced to measure the effects of time-varying scene characteristics on the despeckled dataset. The consistency of the proposed framework is tested on state-of-the-art multitemporal despeckling algorithms.

In this article, we present a fully analytical model for the evaluation of the electromagnetic (EM) field scattered from a composite target in a generic bistatic configuration. The scenario comprises a rectangular parallelepiped target with smooth dielectric faces lying over a rough background surface, modeled as a stochastic process. The single- and multiple-bounce scattering contributions arising from the target, the rough background, and their interactions have been derived under the Kirchhoff approximation (KA)-geometrical optics (GO) solution. This framework enables the evaluation of the bistatic radar cross section (RCS) of the considered composite target via closed-form expressions. The proposed model exhibits good agreement with the literature results based on accurate and well-established numerical methods. Our analytical model is therefore proposed as a valid alternative to numerical techniques, being able to provide reliable results at a negligible computational burden. Finally, the role of the main scene parameters, i.e., target orientation, surface roughness, and polarization in the bistatic RCS of the target, have been analyzed and discussed.

Ocean GNSS-R is successfully being employed to retrieve wind speed from GNSS signals scattered by the sea surface. To obtain a sufficient scattered field intensity from the ocean surface, the receiver acquires data when it is located along the specular reflection direction. However, new applications of GNSS-R are being explored, among which ship-detection. In this case, scattering from the ocean represents the clutter to be suppressed, so that a different geometry, where the GNSS signals are received in backscattering configuration, is preferable to the forward scattering one. In this new geometry, the Geometric Optics, usually employed in the GNSS-R scientific community, is often no more appropriate to model scattering from the sea surface, and different scattering models must be used. To this aim, we here introduce the Polarimetric Two-Scale Model to evaluate the intensity of the GNSS backscattered signal.

Global Navigation Satellite System-Reflectometry (GNSS-R), is succesfully employed for ocean altimetric and scatterometric applications. Recently, it has been suggested that GNSS-R can also be used for ship detection applications. To this purpose, an accurate electromagnetic modeling of the bistatic radar cross section of a ship lying over the sea surface would be very helpful. However, existing models are typically limited to monostatic configurations, thus restricting their applicability in multistatic scenarios, such as GNSS-R systems. In this work, we show a procedure to determine the bistatic radar cross section of a ship target, under the geometrical optics approximation. Numerical results show the impact of the geometry of acquisition and polarization on the bistatic radar cross section.

In this paper, a comparative study of spaceborne Global Navigation Satellite System (GNSS)-Reflectometry for ship detection applications is provided. The analysis is conducted by evaluating the impact of 1) the acquisition geometry and 2) the received signal polarization on ship detectability in GNSS-R data. In particular, the backscattering acquisition geometry is demonstrated to be more suitable for ship detection applications, thus allowing for the detection of 20 m-length ships. Even very large ships are hardly detectable in the conventional forward-scattering geometry. Moreover, receiving right-hand circular polarization is demonstrated to provide significant improvements of the signal-to-noise-plus-clutter with respect to the conventional left-hand circular polarization channel, conventionally exploited in GNSS-R remote sensing. The study is based on a numerical tool for the bistatic radar cross section of the ship, which is presented in a companion paper.

This work reviews and analyses potentially relevant technologies to ensure that the gaps and stakeholder needs for sea ice products are covered. Each variable related to sea ice that presenting gaps using the European EO infrastructure on the horizon (2020-2030) is revised according the stakeholder requirements, together with the feasibility of deploying available technologies on small satellites. A survey of instruments oriented towards sea ice observations in the past and current is presented. Based on this survey technological capabilities in terms of the spatial resolution, swath, mass, power, and data rate are obtained. In order to identify the technologies, numerical scores are assigned based on instrument capabilities. This works concludes with a set of the technologies compatible with small platforms, with the objective to complement the sea ice data products of Copernicus Services.

Synthetic aperture radar (SAR) image interpretation and analysis are heavily affected by the speckle noise typical of coherent acquisition systems. Very recently, a novel despeckling approach based on the exploitation of a priori information about the scattering behavior of the illuminated surface has been presented. The new scattering-based algorithms, named SB-PPB and SB-SARBM3D, represent a scattering-oriented version of the preexisting PPB and SARBM3D algorithms. In this paper, a comparative sensitivity analysis of the abovementioned despeckling algorithms is performed by means of SAR image simulation tools. First, the sensitivity of the filters against the use of different electromagnetic scattering models for the illuminated surface is analyzed. Then, the roles of the digital elevation model resolution and of the coregistration step are also investigated.

Ships and ice monitoring is of key importance in numerous applications, such as maritime traffic control, prevention of illegal activities, climate change studies, and maritime security. In this work, the feasibility of near real-time ocean target detection from a constellation of spaceborne Global Navigation Satellite System-Reflectometry (GNSS-R) images is demonstrated by addressing the two following points: 1) simulation of the revisit time allowed by constellations of GNSS-R instruments; 2) derivation and implementation of an ocean target detector aimed at identifying inhomogeneous features inside the delay-Doppler map. The revisit time is computed by simulating a realistic mission as a function of the constellation size and the number of receiving channels of the GNSS-R instrument. The proposed ocean target detection algorithm consists of four steps — pre-processing, pre-screening, selection, and geolocation — and is validated using actual U. K. TechDemoSat-1 data.

Speckle noise greatly limits both synthetic aperture radar (SAR) data human readability, especially for non-SAR-expert users, and performance of automatic processing and information retrieval procedures by computer programs. Therefore, despeckling of SAR images is an essential preprocessing step in SAR data analysis, processing, and modeling, as well as in information retrieval and inversion procedures. Up to now, one of the most accurate and promising despeckling approaches - among those based on a single SAR image - is the one relying on the nonlocal means concepts. However, at the best of our knowledge, most of the state of the art considers the despeckling problem only within a statistical framework, completely discarding the electromagnetic phenomena behind SAR imagery formation. In this paper, we introduce the novel idea of a physical-based despeckling, taking into account meaningful physical characteristics of the imaged scenes. This idea is realized via the implementation of a physical-oriented probabilistic patch-based (PPB) filter based on a priori knowledge of the underlying topography and analytical scattering models. This filter is suitable for SAR images of natural scenes presenting a significant topography. An adaptive version of the proposed scattering-based PPB filter for denoising of SAR images including both mountainous and flat areas is also developed. The performances of the proposed filter and its adaptive version are evaluated both qualitatively and quantitatively in numerical experiments using both simulated and actual SAR images. The proposed technique exhibits performance superior w.r.t. the standard PPB filter and comparable or, in some cases, superior to the state of the art, both in terms of speckle reduction and texture and detail preservation.

Speckle reduction in Synthetic Aperture Radar (SAR) images is an essential pre-processing step for a correct analysis and interpretation of SAR data. This justifies the huge effort in the image processing community to develop more and more accurate despeckling techniques in order to reduce speckle effects and then improve readability of SAR imagery also for non SAR expert users. Up to now, nonlocal means approaches provide the most promising and effective despeckling performances. In this paper we develop a new non-local means despeckling technique based on electromagnetic scattering mechanisms. The proposed method, based on a physically meaningful similarity criterion for distance evaluation, is theoretically assessed, tested on a simulated SAR image, and compared to the state of the art.

In this paper, we first discuss some general problems and issues concerning Shape from Shading (SfS) from Synthetic Aperture Radar (SAR) images and present the state of the art. Starting from this general discussion, we propose a new perspective and introduce a novel approach to SAR SfS based on fractals. In particular, fractal geometry is used to model the shape of natural surfaces, which are here of concern. The scattering mechanisms are described through solutions suitable for fractal surface models; in particular, the Small Perturbation Method (SPM) is used. Considering a simple SAR image model, the forward model is then inverted via an appropriate and extremely low-computational inversion approach and the underlying topography is estimated. The proposed SAR SfS technique is tested and numerically evaluated using an actual SAR image.