In recent decades, the Earth Observation (EO) wave interaction modelling domain has witnessed a proliferation of both forward and inverse models. These models are developed by the scientific community to understand the relationship between electromagnetic waves and natural surfaces, and to support methodologies for extracting bio-geophysical variables from remotely sensed data. However, the current landscape exposes certain limitations such as the absence of systematic implementation, validation on limited datasets, and a scarce integration with emerging Artificial Intelligence (AI)-based inversion techniques. This manuscript introduces the Wave Interaction Models Exploitation Framework (WIMEX), developed to address these challenges in the frame of an ESA-funded project. Leveraging EO data available today, and exploiting Graphical Processing Unit and parallel computing, the framework proposes a systematic approach to create, validate, and disseminate forward and inverse models. WIMEX aims to offer a flexible development environment supporting the evolving needs of the scientific community.

In view of the launch of the ESA HydroGNSS mission, whose receiver will measure both left and right-polarized global navigation satellite system reflectometry (GNSS-R) signal, this study analyses the features of dual-polarized signals by using simulations provided by the soil and vegetation reflection simulator (SAVERS) over both bare soil and forest. The reliability of GNSS-R dual-polarized simulations of SAVERS over land is first assessed by comparison with data collected in the frame of the GLObal navigation satellite system reflectometry instrument (GLORI) airborne campaigns. Then, the simulator is used to carry out a sensitivity analysis of left–right (LR) and right–right (RR) circularly polarized spaceborne GNSS-R signals to soil moisture (SM), soil roughness (SR), and forest biomass (BIO). The combinations of the two polarizations, such as ratio, difference, and normalized difference, are included in the analysis as well. The study evaluates also the SM effects on the horizontal-right (HR) and vertical-right (VR) polarized GNSS-R signal. The results show that the combination of the two circular polarizations can reduce the small-scale roughness effect in the SM monitoring as well as the effect of topography, and it can extend the sensitivity to large values of BIO. A critical point assessed by this study is the low value of the RR signal power, which may be difficult to detect over the noise floor, especially over land regions with low depolarization effects.

Phase altimetry has been recently introduced for high precision surface height measurements in satellite global navigation satellite system reflectometry. In the presence of coherent scattering the effectiveness of the technique has been demonstrated for sea surface at low grazing angle as well as for rivers and lakes. This study develops the concept of differential phase altimetry for land surfaces, provided that the surface roughness is small and the surface undulations are gentle. Differential phase altimetry is more tolerant with respect to atmospheric and systematic errors but its applicability is difficult in the presence of surface slope variations that may generate phase cycle slips that require complex post processing to unwrap the retrieved phase. To mitigate cycle slips an overlapping correlation process is introduced to generate phase values with high spatial resolution. A first evaluation of performance is presented using the CYclone Global Navigation Satellite System raw intermediate frequency acquisitions over land surface with gentle undulations.

This study focuses on the retrieval of soil moisture (SMC) and forest Aboveground Biomass (AGB), and on the classification of fire disturbances in forests by using the NASA’s Cyclone GNSS (CyGNSS) data over land. Retrieval and classification algorithms, based on machine learning (ML) techniques, as Supported vector machines (SVM), Artificial Neural Networks (ANN) and Random Forests are implemented and validated against reference data from in-situ measurements and EO products.The research, which was carried out in the framework of two ESA project, has the twofold aim of further assessing the potential of GNSS-R for land applications and of defining retrieval concepts to be applied to the ESA’s SCOUT 2 HydroGNSS satellite mission.

Phase altimetry has been recently introduced for high precision measurements in satellite bistatic global navigation satel-lite system refiectometry in the presence of coherent scattering. This work introduces differential altimetry concept via a simulation study. The phase difference between two contigu-ous specular points paths is exploited to reduce atmospheric effects and systematic errors occurring over closely spaced paths. The work also introduces an oversampling technique to mitigate unwrapping errors.

HydroGNSS is the second mission supported by the European Space Agency (ESA) under the Scout program, which is a new framework (3 years from KO to launch, cost ≤ 30 M€) by which ESA aims to demonstrate disruptive sensing techniques or incremental science, while retaining the potential to be subsequently scaled up in larger missions or implemented in future ESA Earth Observation programmes. HydroGNSS consists of a scientific demonstrator that primarily addresses land bio-geophysical variables. The mission is comprised of one satellite (with an option on the second) flying at a low-Earth orbit to collect Global Navigation Satellite System reflections (i.e., Delay Doppler Maps, DDMs) near continuously over the globe. The DDMs are used to generate Level 2 products related to Essential Climate Variables (ECV s), whose estimation defines the primary scientific goal of the mission. In this contribution we outline a review of the ECVs targeted by HydroGNSS, showing some representative results achieved during preliminary studies about the mission. Special emphasis is given to the monitoring of soil freeze-thaw state and soil moisture. ECVs are of great interest and support the sustainable development agenda adopted by the United Nations members in 2015.

We propose an analytical solution of the scattering for the evaluation of the decorrelation time of reflected signals of opportunity. We consider spaceborne receivers and an approximated solution of the covariance of the scattered field under the Kirchhoff approximation. The case of an infinite illuminated surface showing gentle undulations is studied. It is discussed how the near-specular scattering, collected over land targets by a receiver from space, decorrelates as a function of the receiver movement and of the statistical parameters describing the illuminated surface. The study gives information of interest for the design of future bistatic missions, especially for GNSS reflectometry. The interpretation of data from space, which typically shows strong fluctuations, can also be supported.

The GNSS reflectometry (GNSS-R) potential for the monitoring of hydrological parameters as soil moisture (SM) and forest aboveground biomass (AGB) has been largely proved in recent years. In this study, algorithms based on Artificial Neural Networks (ANN) have been developed for the retrieval of both SM and AGB from GNSS-R observations. This activity has been carried out in view of the ESA's HydroGNSS mission. Waiting for HydroGNSS data, the algorithms have been implemented and validated by using the NASA's Cyclone GNSS (CyGNSS) land observations, confirming a promising potential of GNSS-R for the monitoring of both SM and AGB.

A comparison of three different electromagnetic scattering models for land surface delay-Doppler maps (DDMs) obtained from global navigation satellite system reflectometry (GNSS-R) along a Cyclone Global Navigation Satellite System (CYGNSS) track in the San Luis Valley, Colorado, USA, is presented. The three models are the analytical Kirchhoff solutions (AKS), the Soil And VEgetation Reflection Simulator (SAVERS), and the improved geometrical optics with topography (IGOT). Common inputs to the three models were defined by using field samples of soil moisture and texture, soil surface roughness measurements, and a digital elevation model (DEM). The resulting peak reflectivity profiles of the models and the CYGNSS data all had a range of 10 dB along the selected track, mainly due to the influence of topography. The reflectivities obtained from all three models agreed with one another to within 2.4 dB along the full length of the track. The models also showed general agreement with the corresponding CYGNSS data, although the modeled profiles were higher than CYGNSS Science Data Record Version 3.1 by an average of 5 dB and also smoother. Additional characterization of fine-scale surface roughness is identified as an area for future work to improve model fidelity. An intercomparison of DDM structure for three selected acquisitions is also provided.

Signal fluctuations at the receiving antenna have been studied from decades by the radar community, especially to understand the decorrelation of the scattering in radar interferometry. This was done assuming uncorrelated point-like scatterers, leading to a simple model for the geometric decorrelation. In this case, the scattering is certainly incoherent. The quasi-specular reflections gathered under the illumination of signals of opportunity can exhibit significant temporal fluctuations. They are related to the statistical features of the surface roughness and can be observed even in almost flat regions, where a predominant coherent reflection could be expected. The presence of gentle undulations, however, i.e., those showed by surfaces having variations of the profiles comparable with the wavelength over the vertical scale, but much longer over the horizontal one, can determine transition regions where the scattering is neither coherent nor completely incoherent. In these conditions, the nature of the fluctuations of the scattering is not well understood and it requires additional studies. A discussion about the dominance of coherent or incoherent reflection in the Global Navigation Satellite System Reflectometry (GNSS-R) community is presently ongoing. To describe the nature of the scattering, and to understand the decorrelation of the near-specular components in GNSS-R, we propose a numerical study of the field collected by a moving airborne receiver based on the Kirchhoff approximation. Our study demonstrates that the near-specular scattering collected over representative natural landscapes by a GNSS-R receiver is partially coherent and essentially incoherent in most cases. Its correlation time is a function of the roughness parameters, namely standard deviation and correlation length, as well as of the system parameters (i.e., spatial resolution and height). The analysis can provide useful information for the interpretation of GNSS data, which present intrinsic variability that can significantly affect the retrieval of the relevant bio-geophysical parameters.

To understand the temporal decorrelation of the near-specular component of land-scattered signals in global navigation satellite system reflectometry (GNSS-R) and describe the nature of the scattering considering spaceborne receivers at arbitrary altitudes, we propose here an analytical solution of the covariance of the field under the Kirchhoff approximation. Both cases of infinite illumination and finite illumination on the ground are studied. Surfaces with gentle undulations are considered, i.e., those having small slopes and showing slow variations of the profiles over the horizontal scale. This allows for investigating scattered fields that can be neither coherent nor completely incoherent over land surfaces that are nearly flat. In a recent work from the authors, an extensive numerical evaluation of the decorrelation of the near-specular land scattering was presented. The phenomenology of the problem was studied and discussed numerically, solving, for airborne receivers, the relevant scattering integral, both as a function of the geometry of the system and the statistical parameters of the illuminated surface. Such numerical results are used here to validate the proposed closed-form formulation. It is demonstrated how the near-specular scattering, collected over land targets by a GNSS-R receiver from space, decorrelates as a function of the receiver movement and the statistical parameters describing the illuminated surface (namely, height standard deviation and correlation length). The proposed analysis provides information of interest for the design of future GNSS-R missions. The interpretation of GNSS-R data from space, which typically shows strong fluctuations, can also be supported by this approximated analytical study.

Bistatic scattering from rough surfaces is typically approached through the analysis of the scattered field in the conventional H and V polarization basis, which coincides with the zenith and azimuth unit vectors in a spherical reference frame. This study delves into the impacts of different choices of the transmit and receive linear basis on the performance and design of a synthetic aperture radar (SAR) mission receive-only companion. This article formalizes the rotation of the scattered wave orientation at the antenna axes of the companion with respect to the transmitted one and introduces a novel set of linear polarizations, named principal polarizations, in transmit and receive, deemed more suited to represent the scattering mechanisms of rough surfaces. Such a set is defined by the polarization bases that maximize the radar cross section. It is shown that the theoretical estimates from the proposed geometrical framework provide a good agreement with analytical and numerical simulations, performed considering state-of-the-art numerical solutions. In addition, this article promotes the hypothesis that a bistatic radar configuration, defined through the conventional H and V linear basis, presents a strong similarity, from a target information retrieval standpoint, to a monostatic compact$\varphi $-pol mode, i.e., with the transmission of a linear polarization rotated by an angle$\varphi $. The rotation$\varphi $varies over the swath and as a function of satellite separation. For baselines of 250–300 km, such as those envisioned by the European Space Agency (ESA) Harmony Earth Explorer candidate, and for steep incidence angles, an equivalent$\pi /8$-pol can be achieved for rough surfaces.

ALtimetry for BIOMass (ALBIOM) is a Permanent Open Call Project funded by the European Space Agency (ESA) to explore the possibility of forest biomass retrieval by using Copernicus Sentinel-3 (S-3) Synthetic Aperture Radar Altimeter (SRAL) in low- and high-resolution mode at Ku- and C-bands. It represents an original work in the research of new techniques for vegetation observation using altimetry data. Because of the complexity of the land surfaces, no algorithm has been developed for a specific retracking of the altimetric land waveform. This calls for the development of a model able to reproduce the acquisition system and the target scattering phenomena to simulate the interaction of the radar pulse with the land. In this first work we present the electromagnetic simulator of S-3 SRAL altimeter measurements over bare soil scenarios realized through a modification of the SAVERS (Soil And Vegetation Reflection Simulator) simulator developed by the team for GNSS-R reflectometry over land. The impact of topography has been also taken into account. We demonstrate that SAVERS for S-3 SRAL proved its capability to reproduce altimeter waveforms’ main attributes for both flat and topography scenarios.

Forests play a crucial role in the climate change mitigation by acting as sinks for carbon and, consequently, reducing the CO2 concentration in the atmosphere and slowing global warming. For this reason, above ground biomass (AGB) estimation is essential for effectively monitoring forest health around the globe. Although remote sensing-based forest AGB quantification can be pursued in different ways, in this work, we discuss a new technique for vegetation observation through the use of altimetry data that have been introduced by the ESA-funded ALtimetry for BIOMass (ALBIOM) project. ALBIOM investigates the possibility of retrieving forest biomass through Copernicus Sentinel-3 Synthetic Aperture Radar Altimeter (SRAL) measurements at the Ku- and C-bands in low- and high-resolution modes. To reach this goal, a simulator able to reproduce the altimeter acquisition system and the scattering phenomena that occur in the interaction of the radar altimeter pulse with vegetated surfaces has been developed. The Tor Vergata Vegetation Scattering Model (TOVSM) developed at Tor Vergata University has been exploited to simulate the contribution from the vegetation volume via the modeling of the backscattering of forest canopy through a discrete scatterer representation. A modification of the Soil And Vegetation Reflection Simulator (SAVERS) developed by the team for Global Navigation Satellite System Reflectometry over land has also been taken into account to simulate the soil contribution.

Monitoring freeze/thaw variations of the Earth surfaces is of paramount importance for the study of biogeochemical processes and climate change. At present, the use of passive sensors is well established, but, very recently, some studies demonstrated the potentialities of observations exploiting signals of opportunity. We propose here an advanced study to demonstrate the capability of spaceborne Global Navigation Satellite System Reflectometry (GNSS-R) to provide accurate and systematic information about the Earth-surface freeze/thaw state. Reflectivity values derived from TechDemoSat-1 (TDS-1) data are elaborated and compared against the Soil Moisture and Ocean Salinity (SMOS) freeze/thaw product, while state-of-the-art land cover data are used to select GNSS-R data within an estimated footprint. In spite of the limited data availability due to sparse spatial coverage and calibration issues of TDS-1 observations, the proposed analysis demonstrates the possibility of monitoring the freeze/thaw state by analyzing the calibrated reflectivity, including also the possibility of detecting the transition state between frozen and thawed conditions across seasonal variations. This feature makes the design of next-generation GNSS-R satellite missions a unique opportunity to achieve high-resolution freeze/thaw monitoring with small and low-cost platforms.

A comparison of three different electromagnetic scattering models for delay-Doppler maps (DDMs) of global navigation satellite system reflectometry (GNSS-R) from land is performed along a Cyclone Global Navigation Satellite System (CYGNSS) track over a validation site in the San Luis Valley, Colorado, USA. The peak reflectivity profiles of all three models and of the corresponding CYGNSS data are found to be in general agreement and are strongly influenced by topography. An intercomparison of DDM structure for one acquisition is also included. Efforts to refine the model results using a high resolution lidar survey are ongoing.

The Global Navigation Satellite System Reflectometry (GNSS-R) is an emerging remote sensing technique based on the exploitation of scattered navigation signals for monitoring bio-geophysical parameters of the Earth surface. The receiver is placed onboard of airborne or spaceborne platforms, whose movement can affect the feature of the gathered signals. These can present strong fluctuations, which depend on the electromagnetic parameters of the illuminated surface and on its statistical features. Fluctuations have been studied from decades by the radar community, especially to understand the decorrelation of the scattering in radar interferometry. It has been done, however, by only considering uncorrelated point-like scatterers, leading to a simple model. To characterize the temporal decorrelation of the near-specular scattering in GNSS-R systems, we describe here some numerical results collected by a moving receiver changing the random surface parameters and accounting for the coherent/incoherent nature of the scattered field.

ALtimetry for BIOMass (ALBIOM) is a research project funded by the European Space Agency to study the possibility of estimating above ground biomass by means of low- and high-resolution Sentinel-3 altimetry data. We present preliminary results of a sensitivity analysis, developed to assess in what extent waveforms and altimetry observables are affected by the presence of forests. Ku- and C-band altimetry data have been collected and processed to properly select well-tracked waveforms over land, which are then related to collocated biomass data. A statistical analysis has been performed, highlighting a sensitivity of the estimated normalized radar cross section with respect to forest biomass, even though it is strongly disturbed by the soil topography within the radar footprint. Additionally, the inaccurate positioning of the time-tracking window limits the number of useful data.

Monitoring freeze/thaw variations of the Earth surfaces is of great value for the study of biogeochemical processes and climate changes. Over the last decade, the use of passive sensors has been established and, more recently, some researches demonstrated the potential of exploiting observations based on signals of opportunity. We propose an advanced study to assess the capability of spaceborne Global Navigation Satellite System Reflectometry (GNSS-R) to give systematic information about the soil freeze/thaw state of high-latitude regions. To this aim, reflectivity values derived from TechDemoSat-1 (TDS-1) data are elaborated using state-of-art land cover data.

In recent years, the global climate change increased significantly the occurrence and severity of forest disturbances due to fires, causing important alterations in forest ecosystems that also impact on climate and affecting the forest capability of providing resources for human needs. This paper aims at exploiting the potential of Global Navigation Satellite System Reflectometry (GNSS-R), based on L band signals, for the detection of forest disturbances due to fires. The study focused on the forested part of Angola that was largely affected by fires during the summer 2019 and exploited the data collected by the NASA Cyclone GNSS (CyGNSS) constellation. As reference data for developing and testing the method, the ESA CCI decadal burned areas maps have been considered. A simple approach based on the temporal gradient of the GNSS-R observables, namely Signal to Noise Ratio (SNR) and Equivalent Reflectivity ($\Gamma$), allowed identifying satisfactorily the burned areas with respect to the reference data, by enabling the generation of maps every ten days.

The monitoring of the freeze/thaw dynamic of high-latitude Earth regions is of paramount importance for the study of the carbon cycle and the climate changes. Current approaches essentially rely on the use of active and passive microwave remote sensing, while limited work has been dedicated to study the potential of the Global Navigation Satellite System Reflectometry technique based on spaceborne platforms. In this contribution, reflectivity values derived from the TechDemoSat-1 data have been collected and elaborated, to be compared against the SMAP freeze/thaw product. The proposed analysis indicates a significant seasonal cycle of freeze/thaw state in the calibrated reflectivity, thus opening new perspectives for the bistatic L-band high-resolution satellite monitoring of the freeze/thaw state.

The quasi-specular reflection collected under the illumination of signals of opportunity can exhibit temporal fluctuations related to the characteristics of the surface roughness. Even in quite flat regions, gentle undulations, i.e., those comparable with the wavelength over the vertical scale and much longer over the horizontal one, can exist and can significantly affect the temporal pattern of the signal at the receiver. In this contribution, a full-wave model based on the Kirchhoff approximation is adopted to study and characterize the fluctuation of the scattered field. Numerical simulations are developed, while measurements based on an airborne experiment are introduced to corroborate the concept in realistic conditions. The analysis can give interesting information to help the interpretation of GNSS data and their intrinsic variability, especially those collected by means of satellite platforms.

This study aims at assessing the potential of the NASA's Cyclone GNSS (CyGNSS) data for observing SM and forest biomass. As reference values for the comparison, global datasets of Vegetation Optical Depth (VOD) and SM derived from NASA's Soil Moisture Active and Passive mission SMAP have been considered. The results of the sensitivity analysis suggested exploiting the CyGNSS capabilities in estimating VOD and SM by setting-up prototype retrieval algorithms based on Artificial Neural Networks (ANN).

We present and discuss an electromagnetic model for the description of the coherent scattering from bare soils illuminated by a radar system under arbitrary bistatic geometries. The scattering problem is solved under the Kirchhoff approximation (KA) accounting for both the sphericity of the wavefront of the incident wave and the radiation pattern of the transmitting and receiving antennas. We propose here a general formulation and solution of the scattering problem applicable to an arbitrary bistatic geometry. We discuss and demonstrate the importance of our extension for the characterization of the coherent scattering generated in bistatic radar systems, both inside and outside the plane of incidence. The model is validated against the numerical solution of the Kirchhoff integral and, in the case of the perfect plane conductor, by comparison with the image theory. The work is intended to provide a simple methodology to characterize the coherent normalized radar cross section (NRCS) of a rough surface to be used within the radar equation for extended targets, similarly to what is done for the incoherent component. It aims at enabling a local characterization of the coherent scattering in realistic conditions (e.g., in the presence of inhomogeneous and mountainous surfaces), a feature that is particularly important for practical applications, such as the modeling and understanding of the bistatic scattering generated by sources of opportunity and specifically for Global Navigation Satellite System Reflectometry (GNSS-R) related applications.

The reflection of radar echoes collected under both monostatic and bistatic configurations generally undergoes losses of coherence. These can be affected by many factors, depending on both the system features and the illuminated surface, and it should be properly considered for an accurate characterization of the scattering phenomenon. In this contribution, we investigate and discuss the spatial coherence of the bistatic signal scattered by a rough soil when illuminated by sources of opportunity. A simple analytical model accounting for the essential geometry of the system and of the sphericity of the illuminated wavefront is presented, and the spatial decorrelation of the signal collected by a moving receiver is analyzed. The analysis can be of great interest for the design of next-generation satellite bistatic missions and, in particular, for the assessment of the potentialities of earth observation based on Global Navigation Satellite System Reflectometry.

With the recent launch of TechDemoSat-1 and CYGNSS missions, spaceborne GNSS-R data are now available. In order to understand the involved scattering mechanisms, potentialities and limitations of GNSS-R measurements over land, an electromagnetic simulator represents a powerful tool. In this paper, the SAVERS simulator, that was developed and validated on ground based and airborne data, is now upgraded to take account for the important role of the topography in the satellite acquisitions. The Delay Doppler Maps acquired by satellite sensors show a clear topography effect. The reliability of the simulator is here tested over a volcanic area of Chad and compared with the TechDemoSat data.

The electromagnetic scattering generated by agricultural tilled soils can be affected by a strong anisotropic component of the rough-surface profile. An accurate and reliable modeling of the normalized radar cross section, under both monostatic and bistatic geometries, is particularly important and desirable, especially for the correct estimation of the soil moisture content by means of satellite-based observations. In this paper, moving from the modeling so far proposed in the literature, we present and discuss a novel, more general (i.e., 2-D), spectral representation of an agricultural tilled soil, implementing a solution of the scattering based on the first-order small-slope approximation. Comparisons are given with a well-established model based on a 1-D representation of the soil correlation function, accounting for the radiation pattern of the illuminating antenna. The investigation gives new insight on the phenomenology of the bistatic scattering from the anisotropic soil, providing interesting information for the next generation of satellite missions, which foresees the possibility of launching companion satellites carrying aboard a passive receiver collecting the signal transmitted by active SAR-based platforms.

In this contribution, we analyze the bistatic scattering generated by agricultural soils, which can be characterized by a strong anisotropic component of the rough surface profile. A novel spectral representation is proposed in conjunction with a numerical solution of the scattering based on the well-known small-slope approximation. Comparisons are given with different modeling. The investigation provides interesting and novel information on the phenomenology of the bistatic scattering from the anisotropic soil. This is of great interest for the next generation of satellite missions, which foresees the possibility of launching companion satellites carrying aboard a passive receiver collecting the signal transmitted by an active SAR-based platform.

We present an image-domain adaptive likelihood ratio tests (LRT) detector for low-signature target detection in forward-looking ground-penetrating radar. We exploit multiview tomographic images of the scene under investigation to iteratively adapt the statistics of the targets and clutter arising from the interface roughness. Using numerical electromagnetic data, it is shown that the proposed adaptive LRT detector provides significantly lower false-alarm rates compared with its nonadaptive counterpart while providing comparable detection performance.

The capabilities of bistatic radar observations to estimate the wind field over the ocean are investigated in this paper. The work is based on the analysis of simulated data obtained through a well-established electromagnetic model, which accounts for the anisotropy of the ocean's spectrum and of second-order effects of the scattering phenomenon. Both co-polarized and cross-polarized C-band numerical data, obtained considering monostatic and bistatic configurations, are exploited to investigate on the existence of optimal configurations able to minimize the wind vector error estimation. To this aim, the sensitivities of the bistatic normalized radar cross section with respect to both wind speed and direction are accurately investigated and exploited to evaluate the minimum achievable error standard deviation of the estimation. Small and large baselines are analyzed, giving particular emphasis to bistatic geometries constituted by one or two passive receivers aligned along the track defined by the active system. This investigation, originally performed in the framework of the SAOCOM-CS scientific satellite mission, is conceived to accurately assess the potentiality of bistatic observations of the ocean over variable baselines and to gather valuable information for the design of future bistatic satellite missions.

This work aims at defining applications, products and user requirements, as well as the hardware and ground processing design of a companion satellite mission which shall carry aboard a “passive” radar working in tandem with the Argentinian L-band radar developed by CONAE and denoted as SAOCOM. The primary objective (i.e., science driver) of the SAOCOM companion satellite mission (SAOCOM-CS) is forest tomography, which will be carried out by exploiting small baselines between active and passive systems (order of km) changing with time. Conversely, this paper summarizes the investigation carried out for different bistatic radar configurations that are characterized by much larger spatial baselines (up to hundreds of km) and bistatic angles with very large components both in azimuth and in elevation. Soil moisture and vegetation biomass retrieval takes advantage from the combined exploitation of monostatic and bistatic measurements. The retrieval ambiguity related to target azimuthal anisotropy could also be reduced by bistatic observations, like in the case of the ocean surface. The bistatic system shall collect data with suitable directions and polarizations. The expected performances of a multistatic system have been predicted using electromagnetic models.

Forward-looking ground-penetrating radar (FL-GPR) permits standoff sensing of shallow in-road threats. A major challenge facing this radar technology is the high rate of false alarms stemming from the vulnerability of the target responses to interference scattering arising from interface roughness and subsurface clutter. In this paper, we present a multiview approach for target detection in FL-GPR. Various images corresponding to the different views are generated using a tomographic algorithm, which considers the near-field nature of the sensing problem. Furthermore, for reducing clutter and maintaining high cross-range resolution over the imaged area, each image is computed in a segmentwise fashion using coherent integration over a suitable set of measurements from multiple platform positions. We employ two fusion approaches based on likelihood ratio tests detector to combine the multiview images for enhanced target detection. The superior performance of the multiview approach over single-view imaging is demonstrated using electromagnetic modeling data.