In this paper we present a first demonstration of spaceborne L-band SAR Tomography over a forested scenario. To this aim, we process a SAOCOM stack of nine acquisitions with across-track baselines theoretically achieving a vertical resolution around 22 m. To obtain a correct TomoSAR imaging, we phase calibrate the stack by properly accounting for forest volumetric structure, which drives the choice of calibrating with smaller baselines. Finally, we ground steer calibrated TomoSAR to achieve a consistent reconstruction of forest structure above ground and derive a forest height map. Comparison with reference canopy height gives a very good overall agreement, proving the effectiveness of our approach and making the experiment an interesting test-bed in view of future long-wavelength SAR missions.

Repeat-pass interferometric SAR (InSAR) is widely used for a variety of application scenarios, such as terrain displacement and subsidence monitoring or measuring the state of infrastructures. In this context, the development of effective algorithms to detect temporal and spatial changes in the radar targets becomes of paramount importance. Typically, state-of-the-art methods only return the spatial, temporal, or both locations of the occurred changes without any information about the causes. In this article, we present a novel change detection method able to infer not only whether a target has changed and when but also the reason why a change is detected, defining the concepts of definitive and temporary changes (TCs). This is done by jointly exploiting four radar amplitude images and the corresponding six interferometric coherences computed at different temporal baselines. To this aim, we propose a new deep learning (DL)-based framework based on a fully convolutional neural network (CNN) called deep analysis for nonstable InSAR targets network (DANI-NET). The network design and training strategy are driven by explainable AI (XAI) principles. Here, we rely on the development of fully synthetic training and testing datasets by following a robust statistical derivation, which allows for a full understanding of the network outcomes. We evaluate the DANI-NET performance on an independent synthetic dataset and we compare it to the state-of-the-art permutational change detection (PCD), a nonparametric statistical approach, achieving extremely competitive results. Moreover, we also provide a feature analysis on the prediction explainability using the SHAP method. Finally, we apply DANI-NET to two real-case scenarios, by considering a Sentinel-1 repeat-pass dataset acquired over Iceland during the 2023–2024 Sundhnúkur eruptions and a TanDEM-X multitemporal stack acquired over an open-pit mining site. We validate the method over the Iceland dataset, where we compare the predicted lava field extension with external reference measurements. In both cases, DANI-NET produces high-quality results and adds the possibility of investigating the nature of the changes caused by either natural or man-induced phenomena.

The Geostationary Synthetic Aperture Radar (GEO-SAR) concept aims at defining an Earth Observation system able to provide regional coverage with large swaths and subcontinental access with a very short revisit time by exploiting the unique characteristics of the GEO orbit. These peculiar characteristics make GEO-SAR suitable for imaging and interferometry of fast-evolving large-scale phenomena, such as ground motion or water vapor. The design of the orbit for a GEO-SAR is discussed to provide, at one time, wide imaging capability, compensation for the huge power loss due to the distance, and short interferometric revisit. In particular, interferometry imposes constraints on the repeatability of the orbit that are far more restrictive than the control required for telecommunication satellites. Here, two different specific control approaches are proposed to ensure small normal baselines and to maximize angular band overlap between subsequent acquisitions. The first one is based on four control maneuvers per orbit period that exploits tangential, normal, and radial burns, whereas the second one is based on three daily maneuvers that are performed only in tangential and normal directions. The latter assures accurate motion repetition while saving the required propellant mass.

In this work we present a first spaceborne L-band forest SAR Tomography (TomoSAR). We process a stack of 9 real SAOCOM acquisitions over Amazonas, a scenario mostly consisting of tropical rainforest with average tree height of about 25 m to 35 m. We phase calibrate the stack with Phase Linking algorithm, in order to obtain a consistent reconstruction of forest over terrain and compare TomoSAR results with different spectral estimators. We achieve good results with MUSIC spectral estimator, coping with spatial and temporal baselines and compare the upper TomoSAR envelope with LiDAR forest height. The overall agreement is quite good, confirming the effectiveness of our approach.

Developing algorithms to detect temporal and spatial changes in radar targets is paramount. This paper specifically addresses the temporal change detection aspect, introducing a rapid non-parametric Coherent Change Detection (CCD) algorithm named Fast-Permutational Change Detection (F-PCD). The F-PCD identifies temporal Change Points (CPs) in a radar target by recognizing block structures in the coherence matrix, showing great robustness against non-stationary noise sources that generally affect the performance of the standard approaches. Moreover, the F-PCD is characterized by an accelerated inference process, ensuring efficiency without substantial performance loss. The F-PCD algorithm can be applied to different scenarios, for example, where DEM changes happen, e.g., mining sites, volcano eruptions, and earthquakes. For this reason, an example of the F-PCD application on an active open-pit mining site is presented to validate its effectiveness. Moreover, its generalization capability is demonstrated by a multi frequency-geometry analysis conducted on the same mining site. Finally, fully exploiting the F-PCD outcomes contributes to a broader understanding of temporal changes in SAR data and introduces new perspectives for interpreting InSAR datasets.

Along-track constellations of SAR satellites are a promising technology capable of imaging large areas with fine resolution. The enhanced performance is achieved by reducing the sampling frequency of each spacecraft, and the caused aliasing is later solved in processing by combining data from several sensors. This work presents a flexible and robust method to combine the channels based on back-projection. A secondary step further suppresses residual azimuth ambiguities to obtain the proper high-resolution image. The method allows for the incorporation of additional calibration steps before the final signal reconstruction. Testing and validating were accomplished with simulated data using point targets and a realistic scenario.

Coherent multistatic radio imaging represents a pivotal opportunity for forthcoming wireless networks, which involves distributed nodes cooperating to achieve accurate sensing resolution and robustness. This paper delves into cooperative coherent imaging for vehicular radar networks. Herein, multiple radar-equipped vehicles cooperate to improve collective sensing capabilities and address the fundamental issue of distinguishing weak targets in close proximity to strong ones, a critical challenge for vulnerable road users’ protection. We prove the significant benefits of cooperative coherent imaging in the considered automotive scenario in terms of both probability of correct detection, evaluated considering several system parameters, as well as resolution capabilities, showcased by a dedicated experimental campaign wherein the collaboration between two vehicles enables the detection of the legs of a pedestrian close to a parked car. Moreover, as coherent processing of several sensors’ data requires very tight accuracy on clock synchronization and sensor’s positioning—referred to as phase synchronization—(such that to predict sensor-target distances up to a fraction of the carrier wavelength), we present a general three-step cooperative multistatic phase synchronization procedure, detailing the required information exchange among vehicles in the specific automotive radar context and assessing its feasibility and performance by hybrid Cramér-Rao bound.

Nowadays, Synthetic Aperture Radar (SAR) is widely used in heterogeneous fields with aims strictly dependent on the objectives of the application. One of the most common is the exploitation of the Interferometric-SAR (InSAR) to measure millimeter movements on the Earth’s surface, aiming to monitor failures (e.g. landslides) or to measure the health state of infrastructures (e.g. mining assets, bridges, buildings, etc). In this context, developing algorithms to detect temporal and spatial changes in the radar targets becomes very important. This paper focuses on the temporal change detection framework, proposing a non-parametric Coherent Change Detection (CCD) algorithm called Permutational Change Detection (PCD), a purely statistical algorithm whose core is the Permutation Test. The PCD estimates the temporal Change Points (CPs) of a radar target recognizingblocks structurein the coherence matrix, namely new radar objects. The algorithm has been fine-tuned for small SAR datasets, with the specific aim of prioritizing the analysis of the latest changes. A rigorous mathematical derivation of the algorithm is carried out, explaining how some limits have been addressed. Then, the performance analysis on simulated data is deeply accomplished, carried out for the stand-alone PCD and for the PCD compared with a parametric CCD algorithm based on the Generalized Likelihood Ratio Test (GLRT), and with the Omnibus and REACTIV detectors. The comparison with these other algorithms and the stand-alone performance analysis point out the robustness of the PCD in dealing with very noisy environments, even in the case of a single block. Finally, the PCD is validated by processing two Sentinel I data stacks, ascending and descending geometry, of the 2016 Central Italy earthquake.

Formations of small satellites are gaining momentum as an alternative to single Synthetic Aperture Radar (SAR) systems, allowing them to improve performance and reduce costs. Each sensor operates with a low Pulse Repetition Frequency (PRF), so swath size can be kept large, and the strong azimuth ambiguities are later resolved by combining acquisitions from multiple satellites. For proper imaging to be successful, careful calibration of the system and geometric parameters is performed based on the single-channel images. However, ambiguities jeopardize the retrieval of parameters from data; therefore, it is crucial to identify those areas that are inherently ambiguity-free. This paper handles acquisitions that are highly affected by azimuth ambiguities, as in the case of the formation. First, we model the replica’s structure in the focused image and then propose an effective yet simple method to detect such disturbances. Lastly, we demonstrate an improved approach for estimating the along-track baseline by incorporating the aforementioned ambiguity detection scheme. The proposed analysis is validated with simulated data, considering a realistic reflectivity map derived from a COSMO-SkyMed stack.

Along-track (AT) formations of synthetic aperture radar (SAR) satellites are widely discussed in the literature for their ability to solve the trade-off between resolution and coverage. It is usually assumed that all the satellites in the constellation follow the same orbit with a negligible orbital tube since cross-track (XT) baselines introduce major complexity to high-resolution wide-swath (HRWS) imaging. However, addressing the XT issue is crucial for the feasibility of future formation missions, as realistic orbit control conditions and collision risk considerations will surely impose such baselines. This work discusses HRWS imaging with nonzero XT baselines and derives an algorithm for combining the different channels. The approach differs from traditional methods because the combination is done after focusing, where each target is compressed to several pixels. In this manner, one can address the varying elevation locally. Further performance improvement is obtained by a data-driven definition of the forward model, which utilizes the Matching-Pursuit algorithm to identify the significant ambiguities in each area. The proposed method is highly flexible, as it locally adapts the solution to the actual backscatter and elevation of the scene. Validation and testing were achieved by simulations of X-band acquisition, showing promising results.

This paper tackles two open problems concerning automotive Synthetic Aperture Radar (SAR): whether it is possible to develop a fast and efficient focusing routine and assess the effect of multipath on MIMO-SAR images. First, we present a processing technique that enables real-time imaging of the scene under observation. The idea is that the SAR image is already present in the Range-Angle-Velocity (RAV) data cube and must be extracted with a simple 3D interpolation. Unlike standard Doppler beam sharpening techniques, this processor is accurate since it handles range migration and phase curvature. For what concerns the multipath, instead, we introduce a simple yet effective approach to mitigate this issue, which significantly improves the robustness of SAR systems concerning multipath. To showcase the capabilities and potential of our proposed method, we conducted a comprehensive set of experiments utilizing simulated data. The results were not only able to demonstrate the enhancement of robustness of the SAR system in dealing with multipath but also highlighted the ability of our approach to deliver highly accurate and high-quality real-time imaging of the scene being surveyed.

Coherent compact Single-Input-Multiple-Output (SIMO) SAR formations have been studied as an attractive alternative to the standard monostatic SAR systems in terms of resolution and swath size. Significant gain in performance can be achieved given that the along-track (AT) spacing is well calibrated. We propose an innovative solution to the problem of AT position knowledge, using ambiguities of isolated point targets. A theoretical model of the interferometric ambiguity phase is provided, showing the direct relation to the AT baseline. Focusing the ambiguity allows us to increase its intensity, making the algorithm feasible even in the presence of clutter. The achievable accuracy is discussed theoretically and based on simulation.

With the advantages of high spatial resolution, short repeat-pass cycle, and large observation area in Ka-band distributed geosynchronous (GEO) synthetic aperture radar (SAR) systems, its interferometry (InSAR) measurement can fast retrieve high-resolution and high-accuracy digital elevation model (DEM). However, compared to low-orbit systems, it is more difficult and costly for distributed GEO SAR systems to perform tight formation flying at such a high orbit altitude, and, therefore, atmospheric effects, which bring non-stationary and non-Gaussian phase errors, should be taken into account in its repeat-pass InSAR. To address the problems above, a spatial-temporal joint particle filter-based method (ST-PF) for DEM generation by distributed GEO InSAR is proposed in the paper. The proposed ST-PF method is validated under several stationary and non-stationary atmospheric conditions through simulation experiments, and high-accuracy and high-resolution DEMs are obtained. Moreover, the ST-PF method can withstand severe non-linearity in interferometric phases, which result from a relatively small ambiguity height in Ka-band. It is also tested that the mean square error (MSE) of the retrieved DEM is consistent with the posterior Cramer-Rao bound (pCRB) of the estimation problem, showing the validity and the accuracy of the proposed ST-PF method. With various processing parameters, errors, and scene types tested, the method shows good robustness in different conditions.

This article discusses the effect of multipath in automotive radar imaging under different sensor configurations. The study is motivated by the fact that radar technologies are becoming indispensable in the automotive scenario. Many applications such as collision avoidance systems, assisted parking, and driving assistance systems take advantage of radar technologies to accomplish their task. However, one of the main concerns about automotive radars is the possibility of detecting false targets due to multiple signal reflections. In this article, we show how different sensor layouts experience multipath differently. In particular, we demonstrate that with multiple-input multiple-output (MIMO) radars, what really matters is the physical positions of the transmitting and receiving antennas. The monostatic/bistatic equivalent configurations cannot be used to design a system and to simulate an acquisition in the presence of a multipath. We also demonstrate how vehicle-based MIMO-synthetic aperture radar (MIMO-SAR) imaging can generate a bi-dimensional aperture which significantly reduces multipath effects in the focused image, avoiding the detection of false targets. All the theoretical analyses are supported by several simulations where different sensor layouts are tested, and the capability of MIMO-SAR to reject multipath is validated.

With the advent of self-driving vehicles, autonomous driving systems will have to rely on a vast number of heterogeneous sensors to perform dynamic perception of the surrounding environment. Synthetic Aperture Radar (SAR) systems increase the resolution of conventional mass-market radars by exploiting the vehicle’s ego-motion, requiring very accurate knowledge of the trajectory, usually not compatible with automotive-grade navigation systems. In this setting, radar data are typically used to refine the navigation-based trajectory estimation with so-calledautofocusalgorithms. Although widely used in remote sensing applications, where the timeliness of the imaging is not an issue, autofocus in automotive scenarios calls for simple yet effective processing options to enable real-time environment imaging. This paper aims at providing a comprehensive theoretical and experimental analysis of the autofocusrequirementsin typical automotive scenarios. We analytically derive the effects of navigation-induced trajectory estimation errors on SAR imaging, in terms of defocusing and wrong targets’ localization. Then, we propose a motion estimation and compensation workflow tailored to automotive applications, leveraging a set of stationary Ground Control Points (GCPs) in the low-resolution radar images (before SAR focusing). We theoretically discuss the impact of the GCPs position and focusing height on SAR imaging, highlighting common pitfalls and possible countermeasures. Finally, we show the effectiveness of the proposed technique employing experimental data gathered during open road campaign by a 77 GHz multiple-input multiple-output radar mounted in a forward-looking configuration.

Differential SAR interferometry (DInSAR) is a useful technique used to measure small movements and surface deformation. However, ionospheric phase screens are a major error source in multipass terrain observation by progressive scans sar (TOPSAR) interferograms. In this letter, an improved split-spectrum method is proposed. First, the burst used for ionospheric phase estimation is selected through coherence, and then, the ionospheric phase of the burst is estimated based on the split-spectrum method. Finally, the TOPSAR ionospheric space-variable phase in a large scene is obtained through 2-D space-variable fitting, which avoids the complicated processing of splicing between bursts of different periods and reduces the number of unwrapping calculations for large scenes after splicing. The method can ensure that the number of calculations is reduced without loss of accuracy. Sentinel-1 TOPSAR real data processing verifies the correctness of the proposed method.

We discuss a coherent synthetic aperture radar (SAR) formation where$N$identical sensors transmit at the same time, code, and frequency. This is a particular multiple-input–multiple-output (MIMO) configuration, where the transmitted waveforms interfere together, resulting in an illumination pattern that randomly changes in space and time. Similar to the single-input–multiple-output (SIMO) formations, the diversity provided by the$N$receiver phase centers can be used to mitigate this interference and reduce the pulse repetition frequency (PRF) for achieving large swath coverage. The good point, in the MIMO case, is that the signal-to-noise ratio (SNR) gain of the system increases, theoretically, with the square of the number of elements. However, residual spurious sidelobes may appear as ghosts of the multiple illuminators. In practice, the power gain is to be optimized, together with ambiguity rejection, sidelobes, and azimuth resolution. The actual performances achievable by these formations in terms of impulse response function (IRF), SNR, and sensitivity to the precise positioning of the sensors are discussed theoretically and based on simulations.

A coherent formation of$N$identical SAR satellites is considered in this paper. These sensors transmit at the same time, code, and frequency with no synchronization whichever, but for the timing of the arrivals, creating a Multiple Input Multiple Output (MIMO) configuration. The contemporaneous transmission of N signals is expected to result in a reciprocal interference that leads to an illumination pattern that changes in space and time. In spite of this, the increased number of phase centres (w.r.t. single satellite and SIMO cases) can be used to mitigate the interference and to raise the SNR of the equivalent system. The principles of a recombination algorithm are summarized. In order to evaluate the effectiveness of the MIMO reconstruction and to fully characterize the IRF of a MIMO system from a quantitative point of view, new performance figures of merit are defined.

Automated driving requires a huge number of on-board sensors to provide advanced functionalities, from parking assistance to emergency braking and environment mapping for target recognition/classification. While low-cost automotive-legacy radars are mostly used for target detection due to their limited angular resolution, vehicular Synthetic Aperture Radar (SAR) is emerging as a promising imaging solution, provided that the motion is known with high accuracy. This paper assesses the benefits of a navigation-augmented SAR system exploiting multiple on-board sensors, e.g., Global Navigation Satellite System (GNSS), Inertial Measurement Units (IMUs), odometers and steering angle sensors. The results confirm the potential of the proposed multi-sensor-aided SAR system to obtain centimeter-level accurate images of the driving scenario.

Approximately, 30% of the Sentinel-1 (S-1) swath over land is imaged with incidence angles higher than 40°. Still, the interplay among the scattering mechanisms taking place at such a high incidence and their implications on the backscatter information content is often disregarded. This article investigates, through an experimental and numerical study, the S-1 sensitivity to the surface soil moisture (SSM) over agricultural fields observed at low (~33°) and high (~43°) incidence angles and quantifies the impact of the incidence angle on the SSM retrieval accuracy. The study sites are the Apulian Tavoliere (Italy) and REd de MEDición de la HUmedad del Suelo (REMEDHUS) (Spain), which are both instrumented with a hydrologic network continuously measuring SSM. At low incidence angles, results confirm that for crops such as wheat and barley, dominated in C-band by surface scattering, there exists a good sensitivity of S-1 VV to SSM. At high incidence angles, the sensitivity to SSM holds through the combination of the soil attenuated and double bounce scattering. Conversely, over crops dominated by volume scattering, such as sugar beet, the S-1 VV signal is not correlated with the in situ SSM observations, neither at low nor at high incidence. For all the crops, the sensitivity of S-1 to SSM in VH is found significantly lower than in VV. The impact of the incidence angle on the SSM retrieval has been studied with a recursive algorithm based on a short-term change detection approach. An upper and lower bounds for the worsening of the S-1 VV retrieval performance at far versus near range observations have been estimated. In the worst-case scenario, the root mean square error (RMSE) increases from ~0.056 m3/m3, at low incidence, to ~0.071 m3/m3, at high incidence. The mechanism that lowers the retrieval accuracy at high incidence angles is further investigated in the synthetic experiment and its impact on the RMSE is estimated in terms of the volume scattering contribution.

The state-of-the-art techniques have demonstrated that coherence error degrades the performance of synthetic aperture radar (SAR) interferometry (InSAR) for distributed scatterers (DSs). This article aims at fully evaluating the influence of coherence error on DS InSAR time-series analysis. In particular, we present a methodology to increase the estimation accuracy of DS interferometry, with emphasis on spatiotemporal coherence refinement. The motive behind this is that bias removal and variance mitigation of sample coherence matrix impose optimum weighting for estimating phase series and geophysical parameters of interest, whereas maximization of temporal coherence in a reference network can avoid spatial error propagation during the least-squares adjustment. Rather than developing independent processing chains, we integrate this method into SqueeSAR technique and simultaneously take the advantage of StaMPS into consideration. Using simulation and real data over southwestern China, comprehensive comparisons before and after spatiotemporal coherence refinement are performed over various coherence scenarios. The results tested from different phase and displacement rate estimators validate the effectiveness of the presented method.

The paper tackles the problem of the RFI coming from active LEO systems and affecting a nearly-geostationary SAR system (GEOSAR). The GEOSAR considered operates in the X-Band with a low-inclined (zero), low-eccentric orbit, while the interfering systems are the presently operating X-Band LEOSARs. After the definition of the model, based on the link budget equation, it is described the processing exploited to derive the RFI power estimation for the present day scenario and the related performance of the considered system. Finally it is introduced a statistical model aimed to the prediction of the RFI power for a generic (future) scenario.

The paper describes an end-to-end simulator for Geosynchronous SAR data. The tool is composed of two modules: a raw data time domain simulator and a processor for the generation of the L1 products. The simulated raw data include the effects of atmospheric and clutter decorrelation. The end-to-end simulator is a powerful and flexible tool to be used during the system design phase for the verification of the expected performance.

We propose a full Space and Time Coherent Change Detection (ST-CCD) that takes advantage of Sentinel-1 (S1) short interferometric revisit to enhance sensitivity in detecting changes at a fine space resolution. It extends the Generalized Likelihood Ratio Test (GLRT) used for change detection by single baseline images, to the multi-pass, multi-polarimetric stacks of S1 data. Applications are shown for damage mapping after hazards and for agriculture. A preliminary validation is performed by processing data referred to central Italy earthquake in 2016.

More frequent imaging of Earth system processes is recognised as one of the emerging needs in Earth observation. Conventional low Earth orbit satellites are limited in their ability to provide this, whereas satellites in geosynchronous orbit can in principle provide continuous imaging. A new mission design has been developed from studies for a previous geosynchronous radar mission concept (GeoSTARe) to improve its technical feasibility and geographical coverage, and to reinforce its science focus. This new mission (Geosynchronous - Continental Land Atmosphere Sensing System (G-CLASS)) is presented. G-CLASS is in fact a family of missions: we present a version focussed on the diurnal water cycle - G-CLASS:H20 - for which geosynchronous radar has great potential. G-CLASS:H20 is being developed as a proposal for ESA's Earth Explorer programme.

This paper presents an experimental sensitivity analysis of Sentinel-1 (S-1) backscatter to soil moisture (SM) content observed at low (i.e., ~33°) and high (i.e., ~45°) incidence angles over five agricultural fields of an experimental farm located in the Puglia region (Italy). The analysis focuses on the period from March to June 2017 during which 38 S-1 images along ascending orbits were acquired over the site. Results indicate a slight decrease in the radar sensitivity to SM going from low to high incidence with an impact on SM retrieval error that increases from ~5.65 m3/m3% to ~7.63 m3/m3%.

This work investigates the capability of Interferometric SAR (InSAR) technique to monitor the atmosphere. Changes in the Atmospheric Phase Screen (APS) derived by InSAR are strictly related to changes in the atmosphere stratification and to the 2-D distribution of the water vapor columnar content. High spatial/temporal resolution APS maps provide by a SAR geosynchronous satellite (GEO-SAR) can be assimilated into limited area models (LAMs) for a better characterization of the local scale phenomena. As the observation of GEO-SAR are taken with high incidence angles, the path delay is measured along the slant direction (STD) and thus both the observation operator and the Global Navigation Satellite System (GNSS) products used for calibrating the APS must be considered along that direction. In this work, we compare the STD predicted by the Weather Research and Forecasting Model (WRF), and retrieved by a network of GNSS stations with the APS derived from Sentinel-1.

The Sentinel-1 constellation provides high resolution radiometrically calibrated SAR images with 6 days revisit and global coverage. The radiometric calibration was established during the Commissioning Phase exploiting transponders and natural targets. The paper describes the elevation antenna pattern verification based on the S-1 Antenna Model and the necessary refinements performed to achieve the requested radiometric accuracy.

This paper focuses on the detection, from a stack of repeated-pass interferometric synthetic aperture radar (SAR) images, of such changes causing a target to completely lose the correlation between one epoch and another. This can be the consequence of human activities, such as construction, destruction, and agricultural activities, and also be the consequence of hazards, such as earthquake, landslides, or flooding, to buildings or terrains. The millimetric sensitivity of SAR makes it valuable for detecting such changes. This paper approaches two coherent change detection methods: a space coherent, time incoherent one and a full space and time coherent one, both based on the generalized likelihood ratiob (LR) test. A preliminary validation of the method is provided by processing two Sentinel-1 data stacks of 2016 Central Italy earthquake and by comparing the results with the map of damaged buildings in Amatrice and Accumoli made by Copernicus Emergency Management Service.

We study the impact of atmospheric turbulence, specifically the wet tropospheric delay, in that synthetic aperture radar (SAR) with very long integration time, from minutes to hours, and wide swaths, such as the geosynchronous or geostationary SAR. In such systems, the atmospheric phase screen (APS) cannot be assumed frozen in time as for Low Earth Orbit or airborne SARs nor constant in space as for the ground-based SAR. The impact of space-time turbulence on SAR focusing is quantitatively assessed, and a novel focusing method that integrates APS estimation and compensation is proposed. Performances are evaluated as a function of SAR parameters, mainly the wavelength, based on a parametric model of the APS variogram, and results achieved by a simulating realistic scenario are shown.

The availability of accurate trajectory information is paramount for the processing and exploitation of synthetic aperture radar (SAR) data. Considering the particular case of spaceborne SARs designed for repeat-pass interferometric applications, errors in the trajectory translate into phase artifacts that affect the interferometric performance. In this paper, we propose a model-based procedure to calibrate the trajectories of spaceborne SAR systems by the multisquint (MS) phase. The technique allows to estimate the along and the derivative of across track geometric errors. The geometric model of the InSAR phase is derived as a function of positioning errors and the MS phase model as derivative of the InSAR phase geometric model, with respect to the squint angle. We perform a sensitivity analysis of the model in order to define which geometric errors can be estimated by the MS phase, justifying the assumption that the MS phase is very poorly affected by the atmospheric phase screen. We particularly concentrate on the TOPSAR acquisition mode, where the phase is very sensitive to geometric errors. We start from the classical two-image case and then consider the extension to the multibaseline case. Experimental results obtained by processing of interferometric pairs acquired by the Sentinel-1A sensor are reported.

The paper analyzes the problem of achieving a coherent operation in Geostationary SAR (GEOSAR) missions intended for continuous monitoring of land surfaces. In contrast to LEOSAR missions, GEOSAR uses very long SAR integration times (from minutes to hours). Accordingly phase errors due to orbit perturbations, radar master oscillator drift, atmosphere propagation and other sources must be conveniently compensated during SAR processing to avoid image defocusing. A network of Active Radar Calibrators (ARC) distributed on the observed scene is proposed, providing echo envelope and phase observations before Synthetic Aperture Processing. In this way the radar antenna phase center trajectory and other phase error sources can be continuously tracked and compensated using a pyramidal sub-aperture processing approach.

The paper focuses on the decorrelation of natural targets like fields, crops and forests as observed by Radar in time intervals from seconds to months. The models proposed in literature, the exponentials and the Intrinsic Clutter Model, are reviewed and cross-checked by exploiting space-borne SAR data, for C and X band and ground based Radar campaigns in Ku band. Results provides useful information for evaluating performances in applications like Differential Interferometry or focusing over long term, like for geosynchronous SARs.

The paper introduces a couple of techniques for the enhanced processing of TOPSAR data. Both techniques are based on repeated passes of the sensor over the same area. The first technique combines two “de-synchronized” acquisitions, useless for interferometric purposes, to obtain an “enhanced resolution” image of the coherent scatterers in the scene. The second technique exploits the Permanent Scatterers imaged in the overlap between sub-swaths to perform a relative cross-calibration of the TOPSAR beams. Results on real TOPSAR Sentinel-1A data are shown.

Geosynchronous synthetic aperture radar (GEO SAR) is attracting growing interest due to its potential for flexible and frequent imaging over continental areas. Studies are underway to evaluate mission design options and to investigate enabling technologies. This article outlines a method for assessing mission performance which accounts for actual land-cover distributions and weather statistics to derive statistical estimates of mission performance relative to user-defined requirements. A technical challenge is to account accurately for the effects of surface “clutter”: several methods for this are available and will be evaluated. The methodology is outlined. The performance estimates will be used to refine and validate mission design options and to build evidence for the expected benefits of GEO SAR.

We discuss the effects of the clutter on geosynchronous SAR systems exploiting long integration times (from minutes to hours) to counteract for two-way propagation losses and increase azimuth resolution. Only stable targets will be correctly focused whereas unstable targets will spread their energy along azimuth direction. We derive here a generic model for the spreading of the clutter energy based on the power spectral density of the clutter itself. We then assume the Billingsley Intrinsic Clutter Motion model, representing the clutter power spectrum as an exponential decay, and derive the expected GEOSAR signal-to-clutter ratio. We also provide some results from a Ground Based RADAR experiment aimed at assessing the long-term clutter statistics for different scenarios to complement the Internal Clutter Motion model, mainly derived for windblown trees. Finally, we discuss the expected performances of two GEOSAR systems with different acquisition geometries.

Climate change and anthropogenic pressures are expected to reduce global freshwater availability and to exacerbate water crises in the near futures. To manage water crisis, the most common path of the past century has been a “hard-path”, based on centralized structural actions, strongly affecting the environment. This work aims at developing novel adaptive water management control strategies, in a multi-stakeholders context, based on soft-path measures. We focus on the direct, data-driven use of exogenous information to improve the systems anticipation capability. Specifically, the value of snow data in informing water resource systems operation is explored using a model free approach. The underline idea is that information on the snow water equivalent (SWE) in the basin may be relevant to manage the reservoir releases. To this aim SWE estimates are retrieved from SAR COSMO-SkyMed X-band images. The approach is demonstrated on snow-rain fed river basin in the Italian Alps: the Lake Como watershed. Preliminary results show the relevance of snow information to the reservoir management as well as the potential for remote sensed products in data-driven optimization.

The paper provides the description of a flexible frequency domain background clutter simulator for GMTI applications. The clutter module is able to simulate different acquisition geometries, including very high squint cases, and accounts for scene temporal decorrelation. The clutter simulator operates in frequency domain allowing good computational performance. Details on the simulation algorithm and an overview of the simulator results are provided.

The paper proposes two different architectural solutions for a quasi-geostationary monostatic SAR, hosted on-board of a COMSAT satellite, aiming at monitoring water-vapor, for Numerical Weather Forecast on a sub-continental scale, and hazards like hydrogeological landslides and deformations on a local scale. The two architectures address a system that combines an L-band, wide coverage beam, for coarse resolution imaging, and an X-band, spot beam, for fine resolution imaging. The challenge is to allow the X-band spot to be positioned everywhere within the L-band coverage, that should be hold fixed, but exploiting the same wide reflector.

The paper discusses the implementation of a quasi-geostationary MIMO Synthetic Aperture Radar swarm, also defined as ARGOS in [1]. Such system combines the all-time-all-weather image capability of a SAR, with the resolution enhance, robustness and scalability of a swarm and the continuous observation provide by the geostationary orbit. Two C-band concepts are analyzed in details that differ for the image time and azimuth resolution.

This paper concerns the performance of the Flexible Dynamic Block Adaptive Quantizer (FDBAQ), the on-board data compression scheme used by Sentinel-1A (S-1), the C-band Synthetic Aperture Radar (SAR) system for Earth Observation launched on 3rd April 2014. FDBAQ has been designed to deal with the high instrument data rate due to the high spatial resolution and large swath width. S-1 SAR is able to acquire long data take, corresponding to large volumes of data stored on-board. Since FD-BAQ has been implemented for the first time on S-1, the capabilities of such a compression scheme have not been tested on real data before. The purpose of this paper is to present the results of the analysis of real acquisitions acquired after the end of the Commissioning Phase, so in its full efficiency. FDBAQ is compared with the traditional Block Adaptive Quantizer (BAQ) compression scheme in terms of quantization noise level, average bit rate and signal to noise ratio.

This paper presents the results of a RADAR experiment aimed to assess and eventually complement the Internal Clutter Motion model (ICM) provided by Billingsley, for medium and long integration time SAR imaging. Employing a real-aperture rotating antenna ground-based RADAR, rural areas have been observed in different periods of the year according to two different modes, properly designed to obtain short-term and long-term clutter de-correlation analysis. The results showed interesting aspects of the phenomenon. In particular a non-stationary behavior with time, say from minutes to hours, and a day/night characteristic. Furthermore, the experiment showed how, for a long integration time, the model parameters are different from the ones foreseen by Billingsley.

In this paper, we propose a model-based procedure to estimate the accuracy of Sentinel-1 orbit products by the Multi-Squint (MS) phase. The technique exploits the results of single baseline MS analyses collected for each possible master and slave combination in a stack to estimate the absolute orbit error. Accordingly, as first step we state the geometric model of the InSAR phase and the MS phase model as derivative of the In-SAR phase geometric model with respect to the squint angle, then we describe the algorithm to estimate two components of baseline error using the theoretical model. In this paper we focus on the TOPSAR acquisition modes of Sentinel-1 assuming at the most a linear error in the known slave trajectory. In particular, we describe a dedicated methodology to measure baselines accuracy using bursts and swaths overlaps in data acquired by IW and EW acquisition modes. Finally, we suggest a technique to estimate, by a weigthed least-squase inversion, the absolute orbit error of each image in a stack. Experimental results of single and multi-baseline MS analysis obtained on Sentinel-1 data will be displayed.

Ka-band may lead to important applications for the next generation of SAR spaceborne sensors (e.g.: DEM, disaster management, GMTI, subsidence, ocean currents, vegetation height). Nevertheless, the lack of trusted references on backscatter at Ka-band revealed to be the main limitation for the investigation of future applications. The paper, supported by the ESA project “Ka-band SAR backscatter analysis in support of future applications”, is aimed at studying the wave interaction at Ka-band for a widely varying range of targets in order to define a set of well calibrated and reliable KA-band backscatter coefficients. Here, we propose several examples of backscatter data resulting from a critical survey of available datasets at Ka-band. The reliability of the results will be assessed via a preliminary comparison with Electromagnetic Models (EM).

The paper provides a theoretical model for the Geosynchronous SAR focused data, including clutter and atmosphere decorrelation effects. The focused data model is exploited to generate realistic GEOSAR demonstrative products, on the basis of the preliminary design of a regional GEOSAR system. The provided demo products are useful for a preliminary evaluation of the expected system performances.

The Advanced Radar Geosynchronous Observation System is proposed to be a multiple-input-multiple-output synthetic aperture radar (SAR) system hosted on a swarm of minisatellites in quasi-geostationary orbits. The system is made of N iso-frequency sensors, each of them transmitting and receiving the signals. The system would combine the continuous imaging capabilities of a geostationary SAR, gaining a factor N2in signalto-noise ratio (SNR). The real aperture would be achievable in ~40 min, enabling applications so far unseen, such as monitoring fast deformations, landslides, and other applications for emergency and security. Still, the SNR of the long acquisition time would be conserved. The optimal design of the swarm is addressed, in order to trade resolution, coverage, and revisit time.

This paper concerns the performance of the flexible dynamic block adaptive quantizer (FDBAQ), which is the onboard data compression scheme used by Sentinel-1 (S-1), i.e., the C-band synthetic aperture radar (SAR) constellation whose first satellite (Sentinel-1A) has been launched on April 3, 2014. The data rate that results from the fine resolution and the wide swath of S-1 would exceed, without data compression, the S-1 hardware limitations. The FDBAQ has been proposed as an efficient method to reduce the instrument data rate and limit the onboard storage requirement. The capabilities of such a compression scheme have not been tested on real data before. Preflight simulation and analysis were based on a simplified processing scheme and radar backscattering information taken from past missions. The purpose of this paper is to present the first results of the analysis of real acquisitions, comprising thousands of products, in every S-1 acquisition mode, acquired during and after the commissioning phase. Advantages and limits are presented in detail, comparing FDBAQ and the traditional block adaptive quantizer (BAQ) compression scheme, in terms of quantization noise level, signal-to-noise ratio, and average bit and data rates.

In this paper, a numerical method optimizer based on covariance matching is proposed for synthetic aperture radar (SAR) polarimetric calibration. The method makes use of the information provided by a distributed target and a corner reflector in order to jointly estimate the system polarimetric distortion parameters and the Faraday rotation. A preliminary analysis is conducted to show the expected accuracy values and to identify the intrinsic ambiguities of the problem. Results from simulations are shown to assess the accuracy and convergence of the method. Finally, tests have been conducted on stack of repeated full polarimetric ALOS PALSAR images to check the stability of the retrieved distortion parameters in a realistic case.

GeoSTARe is a proposed geosynchronous synthetic aperture radar (GEO SAR) mission as a hosted payload on a commercial communication satellite. GEO SAR missions have been studied for many years because of their potential for high temporal resolution imaging over continental regions. The large range means that longer signal integration times than for low Earth orbit SAR are required and/or large antennas. The GeoSTARe study includes an analysis of potential user applications for the atmospheric and surface data expected, assuming a mission concept of a broad, L-band, fixed beam plus a steerable X-band beam. A system design methodology is used to propose an outline mission design. This is then used to estimate performance accounting for expected surface backscatter in the different wavebands and the likely incidence angles. Results suggest that GeoSTARe is feasible with an antenna diameter of 6 m and electrical power demand of around 2 kW, and that practically all the identified user requirements can be met. Further work is underway to assess the effects of clutter, typical atmospheric perturbations, and image focussing algorithms.

Synthetic aperture radar tomography (TomoSAR) estimates the scene reflectivity along range, azimuth and elevation directions. Even if many works in recent literature deal with this topic, TomoSAR imaging remains a not easy procedure. In this work, the possibility to improve quality of imaging by a priori information is investigated experimentally; in particular we focus on urban scenario where targets of interest are point-like and radiometrically strong. Accordingly, we look for a sparse reflectivity function; this can be obtained minimizing the solution in an arbitrary Lpnorm using the It-eratively Reweighted Least Square (IRLS) algorithm. Based on an experimental comparison among different choices for p, the conclusion drawn is that the usual choice p = 1 is the best trade-off between resolution and robustness to noise. Therefore, L1norm minimization by IRLS has been exploited to perform CS TomoSAR on real data, and we report in this paper first results obtained using COSMO-SKyMed data acquired over an area in Milan, Italy.

The paper evaluates the effects of Atmospheric Phase Screen on focused Geosynchronous SAR data. We derive theoretical models for the resolution, the interferometric de-correlation and the induced clutter in presence of an APS, whose joint time and space power spectrum is modeled as an extension of the Kolmogorov power law. Finally we provide some statistics gathered from a GB RADAR experiment.

In this paper, the impact of the internal clutter motion in GEOSAR acquisitions is analyzed. A nearly zero inclination with low eccentricity geosynchronous orbit is considered and, therefore, long integration, in order of 20-30 min (for 1-2 Km resolution) or even hours (for tenths of meters resolution), is required in order to reach the desired synthetic aperture length and the required along-track resolution. Moderate transmitted powers and antenna sizes are considered in the analysis. The power link budget of a long integration GEOSAR acquisition is presented and the limitations imposed by the clutter decorrelation are studied. The minimum target RCS to assure the correct performance of the system under clutter interference scenarios is evaluated. Finally, experimental data from Ground Based SAR X-band acquisitions will be used to validate the Billingsley model in long integration acquisitions.

We have identified 16 potential scientific applications of a SAR hosted by a geosynchronous satellite - a concept known as GeoSTARe - which would image much of Europe. These applications cover a very wide range of science including: meteorology, the cryosphere, geodetic geophysics, geohazards, flooding and agriculture. Large area coverage by L-band and localized coverage by X-band radars is required, using measurements from differential radar interferometry, interferometric coherence and backscatter intensity. The major advantage of these applications is the very high temporal frequency of observations achievable (a few tens of minutes).

This paper proposes a set of tests that provide necessary and, as far as possible, sufficient conditions for verifying the phase preservation of synthetic aperture radar (SAR) processors. This paper discusses two different test families composed of self-consistency and point-target-based tests. The set of self-consistent tests extends the well-known CEOS-OFFSET to very different acquisition modes, namely, StripMAP, ScanSAR, TopSAR, and SPOTLIGHT, and introduces a new complementary test to check the consistency of the space-variant implementation of a processor. The set of point target tests, based on the analysis of point target simulated data, completes the self-consistent tests by providing a verification of phase accuracy between different bursts and swaths.

This paper addresses the problem of estimating the azimuth antenna pattern by using a set of persistent point scatterers (PPS) retrieved from a stack of interferometric synthetic aperture radar images. This is achieved by means of a maximum likelihood estimation. PPS emerge as a restricted subset of the well known persistent scatterers, for which many applications have been described in the literature. PPS have a more stringent property since they explicitly require an impulsive trend feature; a good degree of isolation from the neighboring targets is further necessary to estimate the antenna pattern by means of digital spotlight focusing. A statistical model for PPS is provided and experimentally validated; the sufficient number of PPSs necessary to get a given accuracy for the azimuth antenna estimation is also suggested. Results using both simulated and real X-band Cosmo Skymed data are eventually illustrated.

This paper focuses on the generation of very high resolution digital elevation models (DEMs) mainly from single-baseline spaceborne synthetic aperture radar (SAR) systems. The stringent requirements on vertical accuracy demand for frequent and accurate measures of the baselines, subject to mechanical vibrations of the boom that may be severe when long booms are exploited. This paper proposes a solution that exploits an existent coarse-resolution DEM, for example, the Shuttle Radar Topography Mission, as a set of ground control points (GCPs). A computational model and an inversion scheme are introduced to jointly take into account the information coming from the grid of GCP and the local shifts measured during image coregistration. The model properly takes account for the quality of the GCP, its location with respect to the target of interest, and the interferogram noise in correspondence to the GCP. A novel “split-swath” approach is proposed to enhance the quality of the baseline estimates. The mode exploits two narrow strips with significant diversity in incidence angle, achieved, for example, by ScanSAR or TOPSAR mode. An example of design is provided by assuming a Ka-band topographic spaceborne SAR mission.

In this paper, the performance of a nearly zero inclination and low eccentricity geosynchronous synthetic aperture radar (GEOSAR) mission for midlatitude (30°-60°) Earth observation is analyzed. The slow motion of such satellites with respect to the Earth's surface makes it necessary to consider long coherent combination of pulses during hours to reach the desired along-track resolution. A system based on moderate transmitted powers and antenna sizes is considered. The necessary sensitivity in such GEOSAR system is obtained from the accumulated energy of the raw data using a pulse repetition frequency above the Doppler bandwidth and a long integration time. Several issues as a result of the long acquisition, such as target and atmospheric phase screen decorrelation, speckle noise impact on the received signal, and satellite station-keeping requirements, are analyzed. The feasibility of such systems to be placed on a broadcasting communication satellite makes nearly zero inclination GEOSAR a low-cost alternative of current SAR missions.

We propose an efficient method for the azimuth compression and Atmospheric Phase Screen estimation of Geosynchronous SAR data. The method is based on the iterative processing of sub-apertures of increasing size, allowing to gradually refine the quality of the focused data and of the estimated APS. The whole processing can be easily parallelized. Results over simulated data are shown.

The paper debates a novel solution for the longterm monitoring of the system polarimetric quality based on radiometrically and polarimetrically stable targets, herewith named Polarimetric Permanent Scatterers (PPS). The technique is completely scene-based and thus cost effective. It allows, aided by the integration with the available Distributed Target (DT) information, for the relative calibration of the channel imbalance and cross-talk parameters. Their complex time-series information is indeed extracted with respect to the absolute unknown values of an arbitrary image of the stack. The performance achieved on a Radarsat-2 stack show that the accuracy is consistent with that returned by DT techniques. The attention shall be however focused on the fact that the more information can actually be extracted thanks to the proposed monitoring method.

In this work, a numerical method optimizer for SAR polarimetric calibration is proposed. The method makes use of the information provided by a Distributed Target and a Corner Reflector in order to jointly estimate the system polarimetric distortion parameters and the Faraday Rotation. The different order of magnitude of cross-talks and Faraday Rotation is exploited to overcome the intrinsic ambiguity related to the problem. Tests have been conducted both on simulated data, confirming the ability of the proposed method to provide realistic estimation of the distortion parameters, even in case of low quality Corner Reflector.

In the above-named article [ibid., vol. 8, no. 3, pp. 537-541, May 2011], an error in equation (4) appears. In it, the value 0.2589 is corrected to 77.6. The error concerns only the transcription of (4), and not the results presented in the letter, where the proper formulation was indeed used. The authors would like to thank the reviewer who helped correct this.

In this paper, we revise the relative radiometric calibration of synthetic-aperture-radar stacks which exploits natural persistent scatterers (PSs). We introduce a new model to estimate a slight error in the sensor pointing in elevation and a new coherent method that makes use of phases evaluated by averaging the complex data on the local window. We show that the proposed approach outperforms the conventional one, as it is mostly insensitive to the “differential” biasing that affects the noncoherent permanent scatterer calibration (PScal). Results from processing COnstellation of small Satellites for the Mediterranean basin Observation (COSMO)-SkyMed and European Remote Sensing (ERS) satellites stacks are presented.

In this paper, a geosynchronous synthetic aperture radar (SAR) (GEOSAR) mission for atmospheric phase screen (APS) retrieval using a long coherent integration of pulses is analyzed. The nearly fixed position of the geosynchronous platforms makes GEOSAR systems suitable for continuous monitoring applications. However, using moderate transmitted powers and antenna sizes, very long integration times up to hours are required. In GEOSAR, the two-way propagation of radar signals can decorrelate significantly due to atmospheric changes during the long data take, resulting in an APS which can cause image defocusing and artifacts. In this paper, the APS effects are analyzed, and an APS correction algorithm from short-term periodic acquisitions (subapertures) of the whole long-term GEOSAR synthetic aperture is described. The results obtained from the APS retrieval algorithm in a simulated GEOSAR acquisition affected by atmospheric decorrelation are presented. Finally, an experimental test of the APS algorithm performance with a long-integration ground-based SAR acquisition is shown.

The paper investigates the impact of propagation in Ka band quality, by considering the case of clear sky and uniform cloud coverage, up to conditions of rain. The additional attenuation is linked to the probability by focusing in Europe at different latitudes. A layered model is exploited for numerical estimation of both the attenuation and the cloud backscatter in case of uniform cloud coverage.

The paper discusses methods for radiometric calibration of repeat-pass interferometric SAR stacks based on Persistent Scatterers. Coherent and non-coherent approaches for the estimation of the radiometric gain are compared. Furthermore, an estimator of the beam pointing in elevation in proposed. Evaluation of performances is carried out basing on both simulated and COSMO-SKYMED data.

In this paper we discuss a preliminary design for a constellation of geosynchronous (GEO) Synthetic Aperture Radars (SAR). The key design concept is to employ one or more pairs of closely-spaced twin receivers flown onboard GEO minisatellites moving with a velocity of few meters per second with respect to the Earth's surface, so as to form a synthetic aperture on the order of few tenths of kilometers twice a day. The employement of closely-spaced receivers would enable the estimation of the temporal gradient of the tropospheric delay via along track Interferometry, resulting in the possibility to coherently integrate the signal over an aperture time on the order of hours. As a result an area as wide as one thousand kilometers could be imaged while providing: i) continuous temporal coverage at coarse resolution (hundreds of meters); ii) high resolution (few meters) imaging and interferometric capabilities two or more times a day by integrating the signal over few hours, thus ensuring high SNR performance (for stable targets) with a transmitted power comparable to currently operated spaceborne SARs.

The purpose of the paper is to estimate the Azimuth Antenna Pattern by using Persistent Point Scatterers (PPS) selected in a stack of interferometric Synthetic Aperture Radar images. Wide angle antenna pattern is estimated from targets spectra by means of a Maximum Likelihood formulation. PPS are considered a restricted subset of the Persistent Scatterers, for which the point-shape feature is further required. A model for PPS is provided and experimentally validated; antenna estimation results are presented for both simulated and real X-band Cosmo Skymed data.

The paper debates an external calibration approach based on the stable natural targets, namely Permanent Scatterers (PS), that can be spotted in the illuminated frame. The method, hereby called PolPSCal, allows for relative calibration of the full 4 by 3 polarimetric distortion matrices (PDMs) affecting the stack images. The algorithm is neither constrained to a particular PDM model (thus its implementation is practically feasible for any SAR sensor) nor to any external information. These latter are eventually demanded afterwards in order to normalize the returned PDM stack to an absolute reference. The PolPSCal mathematical framework is reported, and a performance analysis with concern to the PS detection and the PDM estimates accuracy is carried out on both synthetic data and a 29 images RADARSAT-2 dataset.

In this paper, a high integration gain GEOSAR mission for Earth imaging is presented. The spatial-temporal atmospheric decorrelation issues of a long integration time GEOSAR mission must be carefully studied. The feasibility of a GEOSAR mission for Atmospheric Phase Screen retrieval purposes is studied. The raw data received from several hours of acquisition is divided into sub-acquisitions with integration time on the order of the APS decorrelation time. From each sub-matrix, a low-resolution but enough to sample the spatial variations of the atmospheric map is obtained. The simulated results of the APS retrieval from a GEOSAR acquisition are shown at the end of this paper.

We propose a novel method to select long-term coherent targets from a set of repeated-pass interferometric acquisitions. The major assumption is that targets are so close together to share the same optical path. This leads to an efficient singular-value-decomposition-based estimator of the targets' phase and, then, to PS detection. The estimated phase can be used to define the PS coherence for each image. Being sensitive to acquisition and processing artifacts, the PS coherence is a valuable tool for quality assessment of the interferometric stack. Results are shown with real data sets in both single and full polarizations.

The aim of this paper is the definition of a series of quantitative phase preserving tests that would be a necessary tool to evaluate the performance of different focusing algorithms and to define some necessary conditions to validate their efficacy and precision. The tests have been thought and defined to form a general tool that can cope with a wide number of systems and acquisition geometries.

The paper addresses the problem of finding an optimal estimation of the Doppler centroid for Synthetic Aperture Radar (SAR) data. The original idea is to exploit a bandwidth much wider than the PRF, say 3–5 times, by selecting non-aliased point targets. Non-aliased band of natural and isolated targets with close-to-ideal features is evidenced by spotlight processing of stripmap acquisitions and accurate Doppler centroid is estimated by means of a joint Maximum Likelihood (ML) estimator. Lower bound of the estimate is determined and results on both simulated and real X-band SAR data are shown.

We propose a robust and reasonably fast approach to provide phase estimation and stable target (Persistent Scatterers, PS) detection from a set of repeated pass interferometric acquisitions. The major assumption is that, locally, the PS phase model is decomposed into the separable product of the intrinsic target phase times the optical path, that is common to all the targets in the estimation window. The Singular Value Decomposition (SVD) is exploited to get at one time a fast estimate of the local phase and the detection of stable targets. The estimated phases are then exploited to measure the PS coherence over the whole image or in image blocks. Being sensible to acquisition and processing artifacts, the PS coherence is a valuable tool for automatic image quality assessment. Results are shown with real datasets in both single and full polarization.

The paper proposes a calibration technique based on Permanent Scatterers (PS) for the full-pol L-band and future P-band spaceborne SAR systems. It will be shown how both a radiometric and polarimetric monitoring of the system parameters can be carried out by exploiting the stable targets in the scene. The procedure aims to estimate the overrall system gain, the channel imbalances, and the Faraday rotation angles which must be accounted at such frequencies. The performance achievable by the technique is investigated with concern to the number of images and PSs which shall be supplied to the algorithm in order to meet the desired accuracy requirements.

In this paper a method for calculating the antenna contribution to the Doppler Centroid is presented. The Antenna Doppler Contribution (ADC) is originated by the non idealities affecting the TR modules of the active antenna arrays. It is an undesired effect for SAR applications requiring stringent performances on the Doppler Centroid control capability. The first part of this paper introduces the problem and shows how it is possible to predict the ADC by exploiting a suitable Antenna Model. The second part of the paper presents a comparison between the ADC calculated with an Antenna Model and the ADC retrieved from real ASAR data.

In this paper, the feasibility of a geosynchronous satellite for Synthetic Aperture Radar applications is assessed. The nearly fixed position of geosynchronous satellites offers new features to SAR acquisition such as the continuous monitoring of wide areas with short revisit times. A monostatic dedicated mission, working with moderated antenna sizes and transmitted powers with long integration time (several hours), is firstly presented and the main SAR parameters (PRF selection, power budget, ambiguities) analyzed. The system Point Spread Function is obtained from simulated raw data showing the system spatial resolution in a realistic orbital configuration.

In this letter, we face one of the main issues in ground-based radar applications, i.e., the evaluation and removal of the atmospheric phase screen (APS). The time-varying delay statistics are assessed by means of both radars and meteo simulated data sets and are critically interpreted with particular reference to the entailed compensation issues. A compensation approach based on the available on-site meteo parameters (pressure, temperature, and humidity) is then investigated. The technique proposes an initial calibration step on humidity which leads to significant improvements in the APS removal. The results of the technique are discussed in the case of a real campaign data set (Bolzano, Italy) that covers a temporal baseline of about one week.

A space adaptive flexible block quantizer (SA-FBQ), suited for spaceborne synthetic aperture radar missions, is presented. This quantizer is actually an extension of the flexible dynamic block adaptive quantizer (FDBAQ), proposed in, which, in turn, is an extension of the block adaptive quantizer (BAQ). The BAQ is the optimal quantizer for a homogeneous target. The FDBAQ gets better performances on heterogeneous targets by adaptively selecting the best BAQ according to the local signal-to-thermal-noise ratio: The worst the SNTR, the lower the quantizer rate. The quantizer selection is precomputed in a lookup table (LUT), by assuming a fixed and known probability distribution function (pdf) of the reflectivity$\sigma_{0}$. The SA-FBQ extends further this concept allowing the reflectivity pdf to vary, coping with this by exploiting many LUTs (i.e., quantizer set), each adapted to the local statistics. In this paper, we introduce an algorithm to adaptively find the best set of quantizers constrained on the mean bit rate; we discuss the implementation of the SA-FBQ, and we estimate its performances in comparison with the FDBAQ and the BAQ under different scenarios. Preliminary results are shown by exploiting the worldwide mosaic of C-band reflectivity derived from European Space Agency ENVISAT data and Sentinel-1 system parameters.

SAR data gathered from forested areas collect contributions coming from the vegetation layer, from the ground below and from other scattering mechanisms (SMs). Multi-baseline data allow a tomographic analysis thus retrieving information about the vertical structure of the target. Multi-polarimetric acquisitions enrich the data, providing ways to identify the targets basing on their electromagnetic properties. The joint exploitation of multi-polarimetric and multi-baseline data suggests the possibility of linking the estimation of the vertical structure of different SMs with their polarimetric signature. A formal framework in which this task can be accomplished is provided by the Algebraic Synthesis (AS) technique, which extends the concepts within PolInSAR through the assumption of the Sum of Kronecker Products (SKP) structure. By assuming the presence of two SMs (for example ground and volume scattering), the SKP assumption leads to a cross dependence between the polarimetric and interferometric coherences, in that ground structure is shown to be related to volume polarimetry, and dually volume structure is shown to be related to ground polarimetry. The aim of this paper is to investigate the implications of this cross relation. Experimental results will be shown basing on a data-set of multi-polarimetric and multi-baseline SAR images at P-band acquired by DLR's E-SAR over the Krycklan catchment, in northern Sweden, in the framework of the ESA campaign BioSAR 2008.

The letter introduces a novel quantizer suited for medium to high-resolution synthetic aperture radar (SAR) systems, like the forthcoming SENTINEL-1 SAR. The Flexible Dynamic Block Adaptive Quantization (FDBAQ) extends the concept of the Block Adaptive Quantization (BAQ), used in spaceborne SAR since the Magellan mission, by adaptively tuning the quantizer rate according to the local signal-to-noise-ratio (SNR). A design is presented aiming to optimize the average bit-rate, while constraining the minimum SNR. FDBAQ optimized performance is then evaluated using backscatter maps derived from ENVIronment SATellite (ENVISAT) data.

We present an efficient focusing algorithm for synthetic aperture radar (SAR) data acquired in short bursts by a geometry with a large range spread, i.e., the case of ground-based (GB) SAR. The usual approach for focusing GB SAR data is the polar formatting algorithm, whose computational complexity, however, is quite relevant due to the nonseparability of the kernel. In this letter, we introduce a different format for the focused data, namely, the range-angular domain. Such format keeps the benefit of the polar format that samples data close to the resolution, but allows for the design of a separable kernel in the wavenumber domain. The proposed kernel exploits a modified Stolt interpolation and an efficient space-varying resampling. Results of processing on both simulated and real data are presented.

This letter focuses on estimating the local fringe frequency of the interferometric phase, under the hypothesis of superficial scattering. Starting from the formulation of the maximum-likelihood estimator, a new simplified estimator is derived. Due to computational efficiency and robustness versus model errors, the resulting estimator is suited for large data processing in the presence of model uncertainty. Furthermore, such an estimator can be straightforwardly extended to the multibaseline case, resulting in the possibility to estimate the terrain slope with great accuracy. An application to real data is presented, based on a multibaseline ENVISAT data set.

We propose a calibration method suitable for a set of repeated synthetic aperture radar (SAR) acquisitions that uses both absolute calibrated devices (such as corner reflectors) and stable targets identified in the scene [the permanent scatterers (PSs)]. Precisely, the role of the PS is to extend the initial calibration sequence by monitoring the radiometric stability of the system throughout the whole mission life span. At a first step, this paper approaches the problem of PS-based normalization by an iterative maximum-likelihood method that exploits the stack of complex interferometric SAR images. Two solutions are given based on different assumptions on the PS phases. As a second step, the merging of these estimates with the available calibration information is discussed. Results achieved by experimental acquisitions are shown in two different SAR systems: 1) a C-band spaceborne SAR and 2) a Ku-band ground-based SAR.

This paper is meant to present a statistical analysis of the role of propagation disturbances (PDs), such as those due to atmospheric disturbances or to residual platform motion, in multibaseline synthetic aperture radar (SAR) interferometry (InSAR) and tomography (T-SAR) applications. The analysis will consider both pointlike and distributed targets in such a way as to cover all the cases that are relevant in the applications. In order to provide a tool for the evaluation of the impact of PDs on the analysis of an arbitrary scenario, a definition of signal-to-noise ratio (SNR) will be introduced that accounts for both the presence of PDs and the characteristics of the imaged scene. In the case of pointlike targets, it will be shown that such definition of SNR allows reusing well known results following after the Neyman–Pearson theory, thus providing a straightforward tool to asses phase-stability requirements for the detection and localization of multiple pointlike targets. In the case of distributed targets, instead, it will be provided a detailed analysis of the random fluctuations of the reconstructed scene as a function of the extent of the PDs, of the vertical structure of the imaged scene, and of the number of looks that are employed. Results from Monte Carlo simulations will be presented that fully support the theoretical developments within this paper. The most relevant conclusion of this paper is that the impact of PDs is more severe in the case where the imaged scene is characterized by a complex vertical structure or when multiple pointlike targets are present. As a consequence, it follows that the T-SAR analyses require either a higher phase stability or a more accurate phase calibration with respect to InSAR analyses. Finally, an example of phase-stability analysis and phase calibration of a real data set will be shown, based on a P-band data set relative to the forest site of Remningstorp, Sweden.

We consider a geosynchronous Ku band system, and the defocusing effects due to the temporal and spatial variability of the atmospheric water vapor. Due to the very slow formation of the spatial chirp (minutes or even hours), the temporal change of the local water vapor content could be significant, thus preventing a correct image focusing and the formation of a coherent image. Using GPS and ground based radar data, we estimate and model the spatial temporal correlation function of the water vapor delay. Then, for a given spatial scale, we estimate the maximum time within which the temporal evolution of the water vapor should be carried out, to be able to track its temporal evolution. This requisite constrains both the EIRP and the apparent velocity of the satellite. Then, we evaluate the possibilities of real time ground motion analyses, as a function of the spatial and temporal resolution and the EIRP.

Modern operational and/or high resolution SAR satellite missions impose stringent requirements on on-board data compression such as a higher data reduction ratio, more flexibility, and faster data throughput. A novel approach is flexible dynamic block adaptive quantization (FDBAQ). This method outperforms currently used block adaptive quantization with respect to Signal-to-Noise-Ratio related to the compression ratio. The FDBAQ method allows bit rate programmability with non-integer rates. This allows the SAR information throughput to be optimized for different types of targets and down-link scenarios using a tradeoff between thermal and quantization noise.

In this paper a technique is described for the tomographic characterization of forested areas through multiple SAR observations. This technique is based on a model of the second order statistics of the multi baseline, multi polarimetric, data which accounts for the presence of multiple distributed targets within the system resolution cell. The results of an experiment performed on a real P-band, multi-baseline, fully polarimetric data set relative to the forested site of Remningstorp, Sweden, are reported. Such results show the feasibility of performing a model based tomographic analysis of forests, resulting in a characterization of both the ground and the canopy in terms of elevation, spatial structure, and scattered power.

This paper focuses on multiimage synthetic aperture radar interferometry (InSAR) in the presence of distributed scatterers, paying particular attention to the role of target decorrelation in the estimation process. This phenomenon is accounted for by splitting the analysis into two steps. In the first step, we estimate the interferometric phases from the data, whereas in the second step, we use these phases to retrieve the physical parameters of interest, such as line-of-sight (LOS) displacement and residual topography. In both steps, we make the hypothesis that target statistics are at least approximately known. This approach is suited both to derive the performances of InSAR with different decorrelation models and for providing an actual estimate of LOS motion and topography. Results achieved from Monte Carlo simulations and a set of repeated pass ENVISAT images are shown.

This paper focuses on multi-pass spaceborne synthetic aperture radar interferometry (InSAR) in presence of distributed scattering, paying particular attention to the role of target decorrelation in the estimation process. This phenomenon is accounted for by splitting the analysis into two steps. In the first step we estimate the interferometric phases from the data, while in the second step we use these phases to retrieve the physical parameters of interest, such as LOS displacement and residual topography. This approach is suited both to derive the performances of InSAR with different decorrelation models and for providing an actual estimate of LOS motion and DEM. Results achieved from Monte-Carlo simulations and a set of repeated pass ENVISAT images are shown.

ENVISAT ASAR is successfully operating since March 2002 and resulting ASAR products are operationally distributed to the user community since December 2002. This paper provides an update of the ASAR performance, from the instrument status to the product quality assessment.

In spaceborne synthetic aperture radars (SARs), the orbit curvature may prevent the use of the processor, causing artifacts that depend on both the extent of the orbit arc and the slant range interval. A viable solution has been derived by extending the singular value decomposition-Stolt approach that was proposed for geophysical applications to microwave SAR. The resulting processor has the same simple scheme as the approach but a different (numerical) computation of both the reference and the Stolt interpolation.

This letter focuses on the performance achievable by spaceborne synthetic aperture radar interferometry (InSAR) in the estimation of line-of-sight crustal deformations from acquisitions over a distributed scatterer. Our model is suited for exploiting the hybrid Cramer-Rao bound (HCRB), where the unknowns are both deterministic parameters and stochastic variables. We take into account both target decorrelation and atmospheric phase screen (APS). This approach leads to a viable evaluation of InSAR performance as a function of system configuration, target decorrelation, and APS variance.

This paper introduces a novel ML based approach to channel identification for time variant SIMO (single input multiple output) systems fed by a stochastic process. We focus on the particular case where the unknowns are represented by the channels phases, that find applications in radar interferometry. Starting from the rigorous formulation of the ML estimator, we derive an approximation that makes use of mixers and FIR filters only. The computational efficiency and the robustness versus model errors of the resulting estimator make it suitable for its implementation is an adaptive framework. An application in topography reconstruction from real SAR (synthetic aperture radar) data is presented

In this paper, a novel (according to the authors' knowledge) type of scanning synthetic aperture radar (ScanSAR) that solves the problems of scalloping and azimuth-varying ambiguities is introduced. The technique employs a very simple counterrotation of the radar beam in the opposite direction to a SPOT: hence, the name terrain observation with progressive scan (TOPS). After a short summary of the characteristics of the ScanSAR technique and its problems, TOPSAR, which is the technique of design, the limits, and a focusing technique are introduced. A synthetic example based on a possible future system follows.

We introduce an innovative algorithm that is capable of suppression of strong azimuth ambiguities in single-look complex (SLC) synthetic aperture radar images, to be used both for detected products and for interferometric surveys. The algorithm exploits a band-pass filter to select that portion of the azimuth spectrum that is less influenced by aliasing, the one that corresponds to the nulls in the replicated azimuth antenna pattern. The selectivity of this filter adapts locally depending on the estimated ambiguity intensity: the filter is more selective in the presence of strong ambiguities and becomes all-pass in absence of ambiguities. The design of such filter frames in the Wiener approach with two different normalization options, depending on the use of the SLC image, either for getting multilook averaged detected products or for interferometric applications. Preliminary results achieved by processing ENVISAT Advanced Synthetic Aperture Radar sensor data are provided.

We introduce a novel accurate technique to estimate the Doppler centroid (DC) in ScanSAR missions. The technique starts from the ambiguous DC measures in the subswaths and uses a method alternative to standard unwrapping to undo the jumps in estimates induced by modulo pulse repetition frequency (PRF) measures. The proposed alternative is less error prone than the usual unwrapping techniques. Doppler Ambiguity is then solved by implementing a maximum-likelihood estimate that exploits the different PRFs used in different subswaths. An azimuth pointing of the antenna that does not change with subswaths, or that changes in a known way, is assumed. However, if the PRF diversity is strong enough, unknown small changes in azimuth pointing are tolerated and accurately estimated. This estimator is much simpler and more efficient, than those in the literature. Results achieved with both RADARSAT 1 and ENVISAT ScanSAR data are reported.

The appearance of new synthetic aperture radar (SAR) acquisition techniques based on opportunity sources enhances interest in bistatic geometries. In seismic data acquisition, each source is currently accompanied by up to 10 000 receivers, and in the last two decades, the bistatic geometry has been carefully studied by scores of authors. Rather then introducing new focusing techniques, within the first-order Born approximation (no multiple reflections), seismic bistatic acquisitions are transformed into monostatic ones using a simple operator named "dip move out" (DMO). In essence, the elliptical locus of the reflectors corresponding to a spike in the bistatic survey is forward modeled as if observed in a monostatic one. The outcome of the model, the so-called smile, is a short operator, slowly time varying but space stationary. To transform a bistatic survey into a monostatic one, it is enough to convolve the initial dataset with this smile. Based on the well-known similarity between seismic and SAR surveys, DMO is first described in its simple geometric understanding and is then used in the SAR case. The same processing that is being used for movement compensation can be applied to the bistatic to monostatic survey transformation. Synthetic examples are also provided.

We summarize a technique capable to combine SAR acquisitions in different modes, like scanSAR/scanSAR or scanSAR/SAR, and we presents preliminary results achieved by processing early ENVISAT acquisitions in AP and WSM mode.

We propose a novel technique to estimate the Azimuth Antenna Pattern (AAP) from SAR images. The technique first perform azimuth focusing at enhanced resolution, then selects those scatterers that are less affected by ambiguous returns and finally derive the AAP by spectral analysis. Results achieved by processing ENVISAT-ASAR data are presented.

The algorithm presented is capable of retrieving the correct DC ambiguity and to fit a fine polynomial estimate both on uniform and contrasted scenes. The core of the algorithm exploits a block wise processing: in each block a coarse unambiguous estimate is provided by exploiting both a second order statistic estimator (WDAR) and a higher order technique (MLBF). The final, fine estimate of the unambiguous Doppler is achieved by jointly exploiting the coarse unambiguous estimate with a fine, ambiguous one. The proposed algorithm accounts carefully for large variation of DC with range, like for recent Emergency Backup Mode of ERS and RADARSAT. The final estimate and its confidence is provided by a weighted average of the block measures. Tuning of the weights and additional check ensure robustness. The estimate of the offset frequency constant is then approached and a solution for calibrating its value is provided.

This paper addresses the problem of filtering interferometric synthetic aperture radar (IFSAR) signals in presence of nonplanar topography to mitigate geometrical decorrelation effects. The problem is space-variant. The authors assume knowledge about the scene topography and derive an optimal, minimum mean square error (MMSE), filtering procedure. The algorithm is flexible and, beside the standard stripmap-stripmap interferometry, it may be applied to IFSAR data acquired in any operative mode. For instance, in scan-scan, scan-strip, and scan-spot interferometry. The scene topography contribution may be either derived from an external rough digital elevation model (DEM) or directly estimated from the SAR data. The filtering technique is extended to the azimuth direction to account for possible Doppler centroid decorrelation. Experimental results carried out on real data confirm the validity of the theory and show that this filtering procedure allows the authors to obtain a reduction of the interferometric noise content. Its gain is particularly marked in the cases of steep topography, where application of the standard common band filters could deteriorate the signal quality, or for large Doppler centroid shifts between the two acquisitions.

The paper introduces a parametric model for the power spectrum density of synthetic aperture radar (SAR) interferograms. This model is derived by assuming the interferogram as a stationary frequency-modulated process and by exploiting the statistical description of earth topography provided by multifractal fields. Despite the small number of parameters involved (three to six in most cases), the model has been proven robust and accurate in most of the cases tested. In particular, the parametric probability distribution assumed for ground terrain slopes fitted the actual histogram (derived from existing digital elevation models) in a range of three to five decades. Applications to blind baseline estimation and phase unwrapping are then briefly discussed.

Deals with the focusing of low resolution ScanSAR data, for both detected amplitude images and interferometric applications. The SAR reference is exploited to achieve ScanSAR focusing in conventional techniques. Such techniques provide quite effective compensation of the azimuth antenna pattern (e.g. no scalloping) when the azimuth time-bandwidth product of the ScanSAR echo is large, but fail to do so as the burst shortens, being reduced to an ineffective weighting of the output. The result is an azimuth varying distortion of the focused impulse responses, a distortion that is partly compensated for in the multilook average (not available for interferometric applications) at the price of a reduction in the processed Doppler bandwidth. This paper proposes quite a different approach. A set of short kernels, each suitable for "focusing" at a specific azimuth bin, has been optimized to reconstruct source reflectivity in the minimum mean square error sense. That pseudoinversion converges to the "conventional" focusing when the burst extent is large and for short bursts, edge effects are accounted for. These azimuth-varying kernels can be suitably tuned to meet constraints in the resolution/sidelobes trade-off and have proved capable of providing fairly undistorted output and fine resolution. They better exploit the available Doppler bandwidth, maximizing the number of looks and the interferometric quality. A decomposition is suggested that implements the inverse operator as a fast preprocessing to be followed by a conventional ScanSAR processor.

A technique to get medium resolution (40/spl times/40 m, on the ground), strip-map synthetic aperture radar (SAR) interferograms and coherence maps close to real-time by means of common UNIX workstations or PCs is presented. The requested efficiency is achieved by the following: 1) exploiting the spectral shift principle to reduce the data rate at the cost of some signal loss; 2) exploiting polyphase filters and integer implementation to get azimuth looks; 3) implementing a fast and robust estimator of coregistering parameters based both on amplitude cross correlation and of looks' phase mismatch estimate.

The authors propose a combination of low-resolution (LR) and full-resolution (FR) SAR images for differential SAR interferometry. The principal problem in such a combination is the volume scattering decorrelation that limits the useful baseline of the interferometric pair to very small, impractical values. A technique has been introduced to remove this decorrelation by exploiting a digital elevation model (DEM) of the area imaged. The resulting interferogram has the quality (in terms of coherence or phase noise standard deviation) of a conventional FR interferogram, but reduced geometric resolution. The technique is suited to those differential interferometry applications where the resolution of the "differential" phase field to be monitored is much coarser than that of local topography. As a possible application, they propose a system that exploits the wide swath imaged by low-resolution ScanSAR modes for frequent monitoring of hazardous areas.

A synthetic aperture radar (SAR) is considered, located on a geosynchronous receiver, and illuminated by the backscattered energy of satellite broadcast digital audio or television signals. The principal application of such a passive system could be differential interferometry, since even low spatial resolution coupled to zero baseline would be useful; however, other imaging applications could be envisaged and even some topographic capabilities if a baseline is created by ellipticizing the receiver's orbit. Spatial resolution, link budget, and possible focusing techniques are evaluated.

Usual coherence estimation in SAR interferometry is a time consuming task since an accurate estimation of the local frequency of the interferometric fringes is required. This paper presents a fast algorithm for generating coherence maps, mainly intended for data browsing. The proposed estimator is based on the speckle similarity of coherent SAR data, and is thus independent of fringe frequency. The following advantages, with respect to the usual estimates, are achieved: (a) The estimator is more than 100 times faster, achieved at the cost of a reduced statistical confidence. (b) The estimator is not affected by possible local frequency estimation errors. (c) The estimator can be directly applied to single look detected images. The theoretical derivation of the statistical properties of the frequency independent estimator is carried out in the stationary case. The nonstationary case is then analyzed on real ERS SAR images.

The focusing quality of a SAR processor greatly depends on the accuracy of the system geometry estimate. Sometimes ancillary data do not provide enough accuracy, therefore autofocusing has to be performed to get the finest quality possible. A "residual" azimuth compression is introduced to show how a defocused image can be compensated by means of a monodimensional local operator. The residual transfer function that generates defocusing is then derived. The effects of the defocusing are shown on both a complex single SAR image and a SAR interferogram. SAR interferograms, however, are much more sensitive to defocusing than the single SAR image. Two algorithms have been developed to estimate, and compensate for, the defocusing in both the single SAR image and SAR interferometric cases. The processors select data suitable for estimating focusing parameters from the whole images by exploring Kurtosis (for single image focusing) or coherence (for interferometric autofocusing). The residual, short time-domain operator is then exploited to retrieve the focusing parameter values and, finally, to get the focused image. The limitations and accuracy of the algorithm in terms of parameter estimation are investigated. Experimental results, obtained from different SAR missions, are presented.

The authors discuss an efficient phase preserving technique for ScanSAR focusing, used to obtain images suitable for ScanSAR interferometry. Given two complex focused ScanSAR images of the same area, an interferogram can be generated as for conventional repeat pass SAR interferometry. However, due to the nonstationary azimuth spectrum of ScanSAR images, the coherence of the interferometric pair and the interferogram resolution are affected, both by the possible scan misregistration between two passes and by the terrain slopes along the azimuth. The resulting decorrelation can be significantly reduced by means of an azimuth varying filter, provided that some conditions on the scan misregistration are met. Finally, the SAR-ScanSAR interferometry is proposed: here the decorrelation can always be removed. With no resolution loss by means of the technique presented.

SAR surveys from separate passes show relative shifts of the ground wavenumber spectra that depend on the local slope and the off-nadir angle. The authors discuss the exploitation of this spectral shift for different applications: 1) generation of "low noise" interferograms benefiting phase unwrapping, 2) generation of quick-look interferograms, 3) decorrelation reduction by means of tunable SAR systems (TINSAR), 4) range resolution enhancement, and 5) the combination of SAR data gathered by different platforms (airborne and satellite) for a "long-time coherence" study.>

A particular approach to the azimuth migration of synthetic aperture radar (SAR) data is discussed. It is shown that a slightly defocused SAR image can be corrected by means of a short monodimensional filter with a quadratic phase vs. time characteristic. This kind of processing, called residual migration, has reduced computational complexity and minimal storage requirements compared to conventional focusing techniques. Residual migration is therefore suitable for implementing an efficient SAR autofocusing processor, which usually requires several focusing iterations to get a good image quality.>