Monitoring displacements with interferometric synthetic aperture radar involves, as final processing stage, the detection of persistent/distributed scatterers. Filtering and multilook is adopted to improve the detection performances in non-urbanized areas, where dominant point scattering mechanisms are less frequent. SqueeSAR and CAESAR based detectors were already compared in [1] under the hypothesis of weak and fully correlated scattering. In this work we extend the comparison to account for the presence of scattering decorrelation. The comparison is carried out by analyzing simulated data as well as data acquired by the COSMO-SkyMed constellation. In both cases the detection based on CAESAR outperforms the one based on SqueeSAR.

The development of SAR Interferometry for ground displacement monitoring has led to the implementation of operative services dedicated to the systematic delivery of archives of measurements. The exploitation of such data archives at regional/national scale requires frequently a proper post-processing of the measurements for their correct interpretation. Measurements are in fact provided in the radar line of sight and can be acquired by different angles, recently also with medium inclination orbits. In this work we consider the problem of projecting Differential Interferometric SAR measurements to the ground. We specifically develop a general methodology for linear (i.e., directional) and a planar projection of multi-orbit interferometric measurements, including its particularization to sloping terrains. Presented results highlight that the proposed projection methodology can provide useful and further options for the interpretation of the SAR displacement measurements with reference to the application to landslide monitoring.

The main problem related to Persistent Scatterer (PS) interferometry is the lack of large point clouds in rural areas, although it has proven to be a powerful tool in urban scenarios, especially in monitoring buildings with possible slow temporal deformations. The identification of PSs in low Signal to Noise Ratio (SNR) areas is crucial and can be done using a multiple hypothesis test to detect the possible presence of multiple scatterers [1]. In this paper, we frame this problem by exploiting the Kullback-Leibler Information Criterion (KLIC), developed in [2], to address the design of one-stage adaptive sensing architectures for multiple hypothesis testing problems in PS interferometry. Theoretical analysis shows the equivalence between the algorithm developed in [1] and [2] for a single scatterer. In this context we use the scheme of multiple hypothesis, provided in [2], for both the formalization of rural PS detection problem and its solution.

Airborne SAR data are typically affected by phase distortions arising from subwavelength residual positioning uncertainties (known as the phase screen) when acquired along different tracks. Existing methods commonly leverage on disjoint estimation of the phase screens affecting the phase information of multibaseline acquisitions. An innovative approach for jontly estimating the phase screens across multiple baselines is presented. The outcomes of the applied phase calibration are evaluated through tomographic inversion, thus obtaining a 3D image that captures the vertical characteristics of the scene’s scattering. Specifically, the proposed method was applied to multibaseline P-band SAR data obtained through the AfriSAR campaign conducted over the Lopé tropical forests in Gabon (Africa). A reference LIDAR data acquired over the area of interest has also been used for a qualitative evaluation.

We propose a novel formulation for layover regions identification in SAR imaging, by employing an appropriate parametrization of the ground profile and utilizing differential geometry. It enables the rigorous identification of both the regions undergoing direct and indirect layover. Specifically, the adopted ray casting based approach results in an efficient implementation, since the sequential exploration always remains confined only to regions (which are adjacent to direct regions) actually affected by indirect layover, thus minimizing unnecessary computation. The implemented algorithm for SAR layover regions simulation results to be robust, efficient, and easy to be implemented. High-resolution Cosmo Skymed (CSK) C-band SAR data acquired over the mountainous area is used to illustrate the capabilities of the proposed approach.

SAR interferometry is a well-established ground deformation monitoring technology that has recently enabled the implementation of projects dedicated to the systematic delivery of archives of deformation time series, even at the continental scale. The use of such archives of data for the management of the regional or national territory presumes the implementation of procedures aimed at converting the measurements products useful for the risk assessment. In this work we discuss preliminary results derived by trans-regional archives of deformation measurements for the characterization of slow-moving landslides. We specifically address the problem of implementing procedures aimed at filtering the data and estimating deformation components along the steepest slope direction.

Airborne interferometric data is typically affected by phase distortions originated from subwavelength residual positioning uncertainties (phase screen) when acquired along different tracks. Available methods estimate the phase screen affecting stacks of multibaseline acquisitions, mainly by exploiting single interfograms separately. A novel method for the joint estimation of the multibaseline phase screens is proposed. The results of the implemented phase calibration are analyzed via a tomographic inversion, allowing to obtain a 3-D imaging estimating the vertical characteristics of the scene scattering. Specifically, we processed the multibaseline, fully polarized P-band synthetic aperture radar (SAR) data collected during the AfriSAR campaign in July 2015 over the Lopé tropical forests in Gabon, West Africa. Validation of the 3-D imaging results, supported by reference LiDAR (NASA LVIS) data, allowed demonstrating that the proposed joint estimation method overcomes the classical disjoint estimation solutions.

Advanced Differential SAR Interferometry and specifically Persistent Scatterers (PS) Interferometry have become popular techniques since they offer the possibility of large-scale analysis and monitoring of Earth's surface. In this work, we address the exploitation of widely used interferometric phase filtering method, SquueSAR, for the PS detection within a two-step processing scheme based on a sequence of low and high-resolution processing. We propose a modification of the iterative approach proposed in [1], in order to avoid phase shifts. The effects of the modification quantify in a significan improvement of the detection performances, verified on both simulated an real data.

In the last two decades, satellite Multi-Temporal Differential Interferometric SAR (DInSAR) techniques have become consolidated tools for studying slow-moving landslides. Moreover, the availability of sensors using different band frequencies and the development of advanced processing algorithms have constantly improved. In this work we discuss the first results of an experimental analysis carried out on multi-temporal multi-baseline L-Band data acquired by the newly launched SAOCOM satellites in the framework of the MEFISTO project founded by the Italian Space Agency (ASI), one of the main aims of which was to test the potentiality of multi-frequency (X, C and L bands) DInSAR data processed with different methodologies applied to a multi-scale slow-landslide analysis.

Synthetic Aperture Radar Interferometry (InSAR) with multiple passes is widely used to monitor deformations of the Earth surface. SqueeSAR and CAESAR (Component extrAction and sElection SAR) are two recently proposed solutions for performing an effective multi-acquisition multilook based filtering of interferograms to contrast the effects of phase noise for weak and/or decorrelating scatterers. Both methods can be used specifically at the detection stage in InSAR processing chains characterized by a two-stage/two-scale processing strategy, to increase the coverage of monitored points. In this work, we compare the detection performances of the SqueeSAR-based and CAESAR-based detectors. We address the evaluation of the performances on simulated data in the classical Gaussian scenario. Results of experiments on data acquired by the TSX and COSMO-SkyMED sensors are also included to discuss the advantages of one method over the other in real scenarios.

The integration of Differential Interferometric Synthetic Aperture Radar (DInSAR) displacement data with ground-based monitoring and ancillary multi-source information (deriving from geological-geomorphological-geotechnical analyses and damage surveys to the built-up environment) can nowadays provide a useful support to activities pursuing the management and protection of structures (e.g., buildings) and infrastructure (including roads, bridges, embankments) exposed to slow-moving landslide risk. Indeed, the implementation of the most suitable risk mitigation strategies requires appropriate procedures tailored on the quality and quantity of available datasets and their joint use according to the scope and the related scale of analysis. As a result of a 15-year multidisciplinary joint research activity, this paper presents a multi-scale methodology which is applied to buildings affected by slow-moving landslides located in selected areas of the Cosenza Province (Calabria region, southern Italy).

Among the several applications of multipass InSAR, monitoring of landslides represents one of the most challenging case because of the topographic characteristics, the heterogeneous displacement rates and the frequent presence of vegetation. In this study, we consider the use of multi-frequency InSAR data for the application to case studies located in the North and South Italy.

Basal and superficial displacements of two landslides in overconsolidated clayey soils are being monitored by inclinometers and GPS since 2005, and in some parts of the slope since the 1990s. The mostly North-South (N-S) orientation of the landslide displacements makes monitoring by satellite interferometry a challenging problem. To solve it, COSMO-SkyMed Differential Interferometric Synthetic Aperture Radar (DInSAR) data were analyzed at the scale for which inclinometers and GPS provide clear indication of displacement directions, thus allowing a confident use also of ERS and Envisat data. The kinematic history of the last 20 years of the urbanized area of the landslides was thus reconstructed even where ground-based displacement series were available over short periods or not available at all. The effectiveness of the remedial measures adopted in the area on displacement rates was also evaluated.

This study demonstrates the use of a novel satellite remote sensing approach to map coastal erosion vulnerability in the Italian site of Piscinas (Sardinia). We focused on the land/water transitional ecosystem, to identify potential coastal erosion phenomena. For this analysis, a synergistic approach between multi-spectral satellite data (Sentinel-2) and SAR imagery (COSMO-SkyMed and Sentinel-1B) was exploited. Two vulnerability maps were created: one longterm (2016–2018) and one short-term (wind event). The results confirm how the coastal vulnerability of this site seems to be linked to episodic events, consequently, the dune system of Piscinas might be considered safe from coastal erosion processes.

Decorrelation is a major drawback in Synthetic Aperture Radar (SAR) interferometry (InSAR) processing, causing poor density of measurement points, mainly outside of urbanized areas. SAR Tomography is one of the most suitable multi-temporal InSAR technique for built environment monitoring. Although typically capable of identifying a large number of scatterers, SAR Tomography detectors suffer the assumption of fully coherent scatterer response, which can be restrictive in real cases. In this work we address the test of a detector of partially correlated scatterers on a real COSMO-SkyMed (CSK) dataset, which was previously derived in the literature [1] as a Rao test for the single-look case and is here extended to the multi-look scenario. Experimental results are compared with those achieved by the Multi-look Generalized Likelihood Ratio Test (MGLRT). Both Partial Correlation and MGLRT have been implemented with a fixed multi-look degree.

This paper deals with the combination of multi-pass images obtained by COSMO-SkyMed SAR satellite over the urban area of Napoli. The coherent processing can improve geometric resolution and the image quality of long-term coherent regions. At last, the coherently and incoherently combined images are fused tighter based on the coherence to increase the readability of the low-coherence regions.

Persistent scatterers (PS) interferometry tools are extensively used for the monitoring of slow, long-term ground deformation. High spatial resolution is typically required in urban areas to cope with the variability of the signal, whereas in rural regions, multilook shall be implemented to improve the coverage of monitored areas. Along this line, SqueeSAR and later Component extrAction and sElection SAR (CAESAR) were introduced for the monitoring of both persistent and (decorrelating) distributed scatterers (DS). Multilook generalized likelihood ratio test (MGLRT) is a detector derived in the context of tomographic SAR processing that has been investigated for a fixed multilook degree. In this work, we address MGLRT and CAESAR in the multiresolution context characterized by a spatially variable multilook degree. We compare the two schemes for the multiresolution selection of PS and DS, highlighting the pros and cons of each scheme, particularly the peculiarities of CAESAR that have important implications at the implementation stage. A performance analysis of both detectors in case of model mismatch is also addressed. Experiments carried out with data acquired by the COSMO-SkyMed constellation support both the theoretical argumentation and the results achieved by resorting to Monte Carlo simulations.

Interferometric and tomographic processing at full resolution of data acquired by very high resolution SAR systems allow providing accurate 3-D reconstruction of built environments, as well as deformation monitoring. In this framework, the detection of Persistent Scatterers (PSs) is a fundamental aspect. The exploitation of multiple observation looks (multilook), is an effective strategy which allows improving the coverage of monitored pixels in natural scenarios. In the framework of SAR tomographic processing, the Multilook Generalized Ratio Test (MGLRT) detection scheme has been proposed in literature. In this work we address the potentialities and main issues related to the exploitation of a multiresolution approach for MGLRT detection based on the identification of statistical homogeneous looks.

Use of the SAR image intensity for estimation of waves and wind over the sea surface is rather well-established. Interpretation of surface currents estimated from SAR data is, as reported in literature, a much more complex issue. In this work we summarize a methodology exploited for the analysis of sea surface currents estimated via the Doppler Centroid Anomaly. The analysis is based on the integration of sea surface current data derived from the wind information by means of the wind-Doppler model proposed in [1]. Experiments acquired by the Envisat system over the coastal area corresponding to an acquisition frame located in South of Italy around Naples.

X-Band systems provide Very High Resolution (VHR) SAR data that have important applications in several areas of the risk monitoring. Processing of interferometric VHR SAR data stacks allows the accurate monitoring of deformation affecting buildings. In this work we discuss the application to the monitoring of the Latronico town, a village in South Italy, severely affected by the slow and continuous movement of a landslide. Data are relevant to the COSMO-SkyMed constellation and results are generated via a tomographic processing.

This paper explores the main issue surrounding the multidimensional synthetic aperture radar (SAR) image focusing techniques, suchlike those caused by the atmosphere propagation delays or by residual platform motion. The problem brings unknown contributions to the phases of complex received signal that it is generally independent of acquisitions track to track and leads spreading and defocusing in multi-dimensional space. To deal with these issues, in this paper an auto-focusing procedure based on sharpness optimization of the reconstructed signal has been employed. The main concern about this technique is that sharpness optimization by itself however can introduce unwanted and uncontrollable vertical shifts in the focused image. To tackle this issue, the phase error is estimated by multiple integration of second derivative of the phase with respect to baseline. The estimation of the calibration phase is performed by optimizing contrast or entropy of the vertical profile with the constraint of a zero phase derivative. In this way, unwanted vertical shifts are avoided and the correct height reference is preserved. Experimental results from the proposed method are evaluated by vertical profile reconstruction performance in the controlled conditions by simulated dataset over the forested area and multi-baseline data acquired by ONERA in Guyana in the frame of European space agency's campaign TROPISAR.

Synthetic Aperture Radar (SAR) tomography presents the advantage of multiple stable targets detection within same pixel. Fast-sup-GLRT (generalized likelihood ratio test based on support estimation) algorithm proved to be an ideal compromise between detection capabilities and computational complexity. In this work, a multi-look version of this detector which exploits the advantages of Capon estimation is examined. Statistical analysis of estimation and detection processes are conducted to compare the performances of sequential non-linear least-squares (NLLS) search and Capon filtering of projected data for double PS identification. Main objective is to exploit the super-resolution advantages of NLLS method without the risk of multiple stable targets classification from the same scattering contribution. For the last desiderate, an additional verification is included within the detection step.

High and very-high resolution remote sensing data provided by the processing of Synthetic Aperture Radar (SAR) images via Differential Interferometry techniques (DInSAR) allow detecting ground surface displacements that can be used in monitoring/control of urban areas and integrated within procedures aimed at analyzing the vulnerability of affected facilities (e.g. structures and infrastructure). In this regard, this paper presents the results of a study that combines DInSAR data and information gathered from damage surveys to buildings interacting with slow-moving landslides. In particular, relationships between cause (DInSAR-derived differential settlements of buildings) and effect (recorded building damages) are retrieved and empirical fragility and vulnerability curves (to be used for damage forecasting purposes) are generated. Considering the encouraging outcomes, the adopted methodological approach can be successfully integrated within a more general framework for the management of slow-moving landslide risk to which urban areas are exposed.

This paper deals with the compensation of phase miscalibration in the general context of tomographic synthetic aperture radar image focusing. Phase errors are typically independent of one acquisition to the other, thus leading to a spreading and defocusing in the multidimensional (3-D, 4-D, and 5-D) imaging space. Coping with this problem in presence of volumetric scattering is generally a complex issue. In this paper, we consider the approach for phase calibration characterized by the advantage, with respect to classical phase calibration algorithms, of not requiring either the identification of a reference target or specific assumptions about the unknown phase function, or a priori information about the terrain topography. The novelty of the proposed phase miscalibration estimation and compensation method is related to its ability to avoid unwanted and uncontrollable vertical shifts in the focused image. The estimation of the calibration phase is performed by optimizing the contrast or the entropy of the vertical profile with the constraint of a zero phase derivative. Such a constraint preserves the output height distribution. Experimental results of simulated and real data are included to demonstrate the effectiveness of the proposed method.

Persistent scatterer (PS) interferometry and more recently synthetic aperture radar tomography have shown to be powerful tools in urban scenarios for providing 3-D point clouds in the reconstruction of buildings as well as in the monitoring of their possible slow temporal deformations. The detection of PSs represents a fundamental aspect, which in the literature has been mainly addressed at full resolution (single-look detection), thus considering only the scatterer coherence properties along the different acquisitions. In this paper, we investigate the benefits offered by the usage of multiple observation looks. Multi-look generalized likelihood ratio test detection schemes are derived and analyzed in terms of detection performances. The analysis shows that even a slight multi-look can provide a dramatic improvement on the detection capability both on simulated and real data, especially in the areas characterized by a low signal-to-noise ratio and in the presence of a limited number of acquisitions.

Synthetic Aperture Radar (SAR) Tomography is a multi-temporal technique which can reconstruct the 3D profile of a scene. One of its main features consists in the ability to detect the presence of multiple Persistent Scatterers (PS) within the same resolution cell. This paper aims to investigate the super-resolution capabilities of SAR Tomography, by detecting targets situated at a distance which is close to Rayleigh resolution. Elevation positions of scatterers are determined with Capon estimation, which is characterized by higher side-lobs reduction. An adapted form of multi-looking is proposed for extraction of targets contribution from reconstructed reflectivity functions and for estimation of reflectivity power textures. An algorithm for detection of dominant and secondary PSs will be conducted based on the derived reflectivity estimates, trying to preserve the advantages of Capon filtering used for reflectivity reconstruction.

Sparse Representation and Compressive Sensing (CS) theory has gained an increasing interest during the last years in many application fields, including SAR tomography. The latter offers the possibility to perform a focusing, beyond the classical 2D (azimuth-range) domain, along other dimensions: f.i., elevation and velocity. The literature, however, lacks of an assessment of the improvement of CS over classical point cloud detection schemes based on the Generalized Likelihood Ratio test which, in the simplest form, use basic beamforming (matched filter) detection based schemes. This work aims to provide a contribution along this line.

This letter deals with inverse synthetic aperture radar (ISAR) autofocusing of noncooperative moving targets. The relative motion between the target and the sensor, which provides the angular diversity necessary for ISAR imagery, is also responsible for unwanted range migration and phase changes generating defocusing. In the case of noncooperative targets, the relative motion is unknown: the ISAR needs, hence, to implement an autofocus step [motion compensation (MoCo)] to achieve high resolution imaging. This task is typically carried out via the optimization of functionals based on general image quality parameters. In this letter, we propose the use of a fast and accurate MoCo algorithm based on the estimation of the Doppler parameters, thus fully coping with the nature of the imaging system. The effectiveness of the proposed method is proven on both simulated data and data acquired by operational systems.

The main advantage of Synthetic Aperture Radar (SAR) Tomography over classical interferometry consists in capacity to detect the presence of multiple scatterers within the same resolution cell. In this paper we present an algorithm for detection of Persistent Scatterers (PS) based on the variation of reflectivity function in elevation direction reconstructed with Beam-Forming technique. Then, we extract the contribution of dominant scatterers from each resolution cell and reapply the detection algorithm to identify the presence of secondary PSs in scene's pixels. The methods were implemented on a dataset of high-resolution Single Look Complex (SLC) images acquired by TerraSAR-X sensor, on which the residual component of interferometric phase was estimated and compensated locally.

The paper summarizes the state-of-the-art and the current and future trends of advanced SAR interferometry and tomographic SAR, the latter also extended to the area known as multidimensional SAR imaging.

This work aims to describe the characteristics and the status of development, including the results of a first preliminary testing campaign, of a low frequency airborne imaging radar developed in Italy for the Italian Space Agency.

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

Feasibility of derivation of sea surface currents from SAR images has been already shown in several experiments. To our knowledge no examples are provided with reference to sites such as Mediterranean coastal areas where the sea surface currents are characterized by lower intensities. In this work we investigate the possibility to exploit SAR data in the coastal area around Naples where archives of regularly acquired data are available.

Interferometric and particularly tomographic processing at full resolution of data acquired by very high resolution SAR systems allows accurate 3D imaging and monitoring of buildings and infrastructures. Recently it has been shown that implementing a light data multilooking leads to a dramatical increase of the density of monitored pixels. In this work we investigate different options for performing the the multilook operation in SAR Tomography and we analyze their performances in terms of detection capabilities of single scatterers.

In order to retrieve information about the sea surface velocity in coastal Mediterranean regions from Synthetic Aperture Radar (SAR) data, in this work we exploit spaceborne as well as airborne data. In particular, we apply two different processing techniques. The first one exploits a single SAR image, whereas the second one, referred to as Along-Track SAR Interferometry, exploits SAR data pairs. The first technique has been applied to spaceborne ENVISAT-1 SAR data, whereas the second one has been applied to airborne data acquired by the Italian InSAeS4 X-band SAR system.

The work addresses the problem of compensating the distortion effects induced by the translational motion of moving targets in Inverse Synthetic Aperture Radar (ISAR) imaging systems. The ISAR motion compensation is the most crucial step in the Autofocusing ISAR technique; this task is typically solved by implementing exhaustive search algorithms by adopting proper functionals based f.i. on image entropy or image contrast. In this work, we discuss an innovative and fast motion compensation procedure that is based on the estimation of two Doppler key Parameters: the Doppler Centroid and the Doppler Rate, which are related to the target motion parameters. The effectiveness of the proposed method is tested on real data acquired by a static Frequency Modulated Continuous Wave radar with an azimuth wide beamwidth; the radar is installed near the inner harbor of La Spezia (Italy) and it owned to the Centre for Maritime Research and Experimentation of the North Atlantic Treaty Organization (CMRE-NATO).

Synthetic aperture radar (SAR) tomography has been strongly developed in the last years for the analysis at fine scale of data acquired by high-resolution interferometric SAR sensors as a technique alternative to classical persistent scatterer interferometry and able to resolve also multiple scatterers. SqueeSAR is a recently proposed solution which, in the context of SAR interferometry at the coarse scale analysis stage, allows taking advantage of the multilook operation to filter interferometic stacks by extracting, pixel by pixel, equivalent scattering mechanisms from the set of all available interferometric measurement collected in the data covariance matrix. In this paper, we investigate the possibilities to extend SqueeSAR by allowing the identification of multiple scattering mechanisms from the analysis of the covariance matrix. In particular, we present a new approach, named “Component extrAction and sElection SAR” algorithm, that allows taking advantage of the principal component analysis to filter interferograms relevant to the decorrelating scatterer, i.e., scatterers that may exhibit coherence losses depending on the spatial and temporal baseline distributions, and to detect and separate scattering mechanisms possibly interfering in the same pixel due to layover directly at the interferogram generation stage. The proposed module allows providing options useful for classical interferometric processing to monitor ground deformations at lower resolution (coarse scale), as well as for possibly aiding the data calibration preliminary for the subsequent full-resolution interferometric/tomographic (fine scale) analysis. Results achieved by processing high-resolution Cosmo-SkyMed data, characterized by the favorable features of a large baseline span, are presented to explain the advantages and validate this new interferometric processing solution.

This paper addresses the problem of focusing moving targets in synthetic aperture radar (SAR) images. This task is solved here by using an inverse SAR (ISAR) technique. The ISAR technique performs an autofocus procedure by implementing exhaustive search algorithms, which are improved by classical convex optimization, of functions based on image contrast or entropy. In this paper, we discuss the possibility to perform an autofocus ISAR technique by exploiting the estimation of the target Doppler parameters, namely the Doppler centroid and the Doppler rate, which are related to the target motion parameters. The present algorithm is based on the reuse of efficient autofocus approaches that are classically used in direct SAR imaging. The effectiveness of the proposed method is tested on COSMO-SkyMed Spotlight SAR data of maritime targets. Furthermore, the proposed Doppler parameter estimation algorithm is compared with a well-known ISAR technique, namely the image-contrast-based technique.

In the last years spaceborne Synthetic Aperture Radar (SAR) Tomography has been successfully exploited for the analysis of complex scenarios, such as urban areas and infrastructures. In this work a novel method is investigated to achieve improved multidimensional tomographic reconstructions of built structures at a fine scale: it exploits a preliminary data filtering stage carried out via the Component extrAction and sElection SAR (CAESAR) algorithm, based on the application of the Principal Component Analysis (PCA) with a reduced multilooking degree. Experimental results obtained by applying this technology to COSMO-SKYMED data are shown.

The work addresses the problem of focusing moving target in very high resolution Synthetic Aperture Radar (SAR) images. This task is here solved by using an Inverse Synthetic Aperture Radar (ISAR) add-on approach. The ISAR technique performs an autofocus procedure by implementing exhaustive search algorithms of functions based on image entropy or contrast. The algorithm discussed in this work is based on the re-use of autofocusing technique classically adopted in SAR focusing. The effectiveness of the proposed method is tested on COSMO-Skymed Spotlight SAR data of maritime targets.

In the spotlight mode the imaging platform steers the antenna to increase the illumination interval of a target to the aim of achieving very high-resolution images at microwave frequencies. The steering is carried out by beam switching on bursts during the data acquisition interval. Due to the change of the beam orientation over bursts, phase shifts can occur from burst to burst. Phase shifts can be also due to the atmosphere in very long integration intervals. In this work we propose a procedure, based on the image contrast maximization technique, able to estimate and compensate such phase shifts. The effectiveness of the proposed solution is demonstrated by its application to real data acquired by the COSMO-SkyMed sensor.

Modern spaceborne synthetic aperture radar sensors are able to operate the spotlight mode to achieve very high resolution images at microwave frequencies. This mode is characterized by antenna steering to increase the illumination interval. The steering is carried out by beam switching on bursts during the data acquisition interval. In addition to an unavoidable spectrum modulation in azimuth, phase shifts can occur from burst to burst. In this letter, we describe the problem and a procedure able to estimate the phase shifts based on the image contrast maximization technique for subsequent compensation at the data focusing stage. Results on real data acquired by the COSMO-SkyMed sensor demonstrate the effectiveness of the proposed solution.

Multidimensional synthetic aperture radar (SAR) imaging is a technique based on coherent SAR data combination for space (full 3-D) and space/deformation-velocity (4-D) analysis. It extends SAR interferometry and differential interferometry concepts, offering new options for the analysis and monitoring of ground scenes. In this paper, we consider the problem of detecting scatterers showing partial correlation properties induced by simultaneous acquisitions from satellite formations or an uneven temporal distribution of satellite constellations. To this end, we first provide a general model for the pixel imaged by a multidimensional SAR system. Then, we design a constant false alarm rate (CFAR) decision rule accounting for the presence of partially coherent scatterers. At the analysis stage, we assess the performance of the new detector also in comparison with a previously proposed CFAR scheme, developed in the context of SAR tomography for fully coherent scatterers.

Atmospheric propagation delay is a key error source in DInSAR processing and represents a main limitation to the use of DInSAR in emergency conditions. Current X-Band sensors, characterized by frequent passes, are even more affected by such problems. In this work we discuss a procedure based on the use of information extracted from GPS data.

In this paper a novel procedure for the filtering of interferograms based on the extension of SAR Tomography on multilook data is presented. This algorithm, named “Component extrAction and sElection SAR” (CAESAR) takes advantage of Principal Component Analysis to handle temporal and angular decorrelation effects as well as of SAR Tomography principles to solve the distributed layover at the interferogram generation stage. Results on Cosmo-Skymed real data confirm the effectiveness of the proposed procedure.

In this work we focus on the Precise Topography- and Aperture-dependent algorithm, briefly PTA, proposed in the recent literature to remove the residual errors still affecting airborne SAR data focused with standard two-step Motion Compensation algorithms. More specifically, we first show that the azimuth-to-frequency mapping used by the PTA procedure is not fully appropriate, because it does not account for the presence of the residual motion errors themselves. Then, we show how to calculate the correct azimuth-to-frequency mapping able to fully account for the presence of the residual motion errors. Finally, we show how to modify the original PTA in such a way to properly exploit the correct azimuth-to-frequency mapping previously discussed.

The new generation of synthetic aperture radar (SAR) sensors is providing images with very high spatial resolution, improved up to the meter scale. Such a resolution increase allows more accurate monitoring capabilities by means of interferometric approaches. The use of higher frequency enhances the sensitivity of the system even to minute changes, such as thermal dilations. This phenomenon has an impact on the interferometric products, particularly on the deformation velocity maps, if not properly handled. Man-made structures, such as steel core bridges and specific buildings, may be very sensible to thermal dilation effects. By extending the multitemporal differential interferometry SAR processing chains, in our case based on the multidimensional imaging (MDI) approach, an additional parameter related to temperature differences at acquisition instants, the thermal coefficient, can be accurately estimated. This parameter provides interesting perspectives in application to infrastructure monitoring: It brings information about the thermal behavior of the imaged objects. In this letter, we investigate the thermal response of the Musmeci bridge (Potenza, Italy), by experimenting the extended MDI approach on a real TerraSAR-X data set. Results highlight the possibility of such a technique to obtain measurements of the motion that is highly correlated with temperature, thus providing useful information about the static structure of bridges.

Airborne synthetic aperture radar (SAR) raw data are affected by motion errors. These are commonly accounted for via standard two-step motion compensation (MOCO) algorithm followed by the Precise Topography- and Aperture-dependent (PTA) procedure proposed some years ago. In this letter, we show how the azimuth-to-frequency mapping used by the PTA approach should be modified to fully account for the presence of uncompensated motion errors.

The new generation of synthetic aperture radar (SAR) sensors is providing images with very high spatial resolution, up to the meter scale. Such an increase of resolution allows a more effective monitoring of ground structures by means of interferometric approaches. SAR-tomography-based approaches use not only the phase but also the amplitude of the received data: they have shown better capabilities with respect to classical persistent scatterers interferometry approaches in monitoring ground scatterers in terms of detection and estimation accuracy and offer the possibility to resolve multiple scatterers. First results on TerraSAR-X data have demonstrated impressive capabilities in the reconstruction of single buildings and in the monitoring of their deformation. However, the use of higher frequency increases the sensitivity of the system even to minute changes such as thermal dilations. In this paper, we address extension of tomographic based approaches to the monitoring of structure thermal dilation. Aspects related to the coupling of estimated deformation parameters, and in general of the estimation accuracy, as well as problems of scatterers detection are deeply investigated. Results on real data are shown to demonstrate the capability of the technique to distinguish linear deformation and thermal dilation and to increase the quality of the monitoring, as well as to highlight coupling effects.

We present a research project, funded by the Italian Space Agency (ASI), aimed at performing 2D and 3D Focusing of COSMO/SkyMed (CSK) SAR Data. We describe the main objectives of the project, briefly illustrate employed techniques, and finally present the obtained results. The latter show that sub-meter resolution can be achieved in the enhanced spotlight CSK acquisition mode, and that by using 3D focusing it is possible to resolve scatterers at different slant heights within the same range-azimuth resolution cell, even in areas characterized by severe height discontinuities and large thermal dilations effects.

We present an adaptive filtering algorithm for accurate estimation of differential interferometric phase and coherence, in order to better support the SBAS approach. The typical method to enhance interferograms is a simple boxcar multilooking, that improves the signal-to-noise ratio (SNR) at the expense of the spatial resolution. The presented technique is based on an adaptive space filter that identifies and averages statistically homogeneous pixels in a given neighbourhood. It also consists of a phase filtering operation in the time domain via the temporal multilink for recovering the consistency of the interferometric phase (phase triangulation). Results on real Cosmo-SkyMed data, acquired over the city of Naples, are shown in order to demonstrate the effectiveness of the presented technique.

This paper describes the capabilities of the TELAER X-Band airborne SAR system, which has been upgrading according to a Italian National Research Council (CNR) funding. Such a system upgrading consists first of all in the realization of a multi-antenna system able to carry out, simultaneously, Across-Track (XT) and Along-Track (AT) SAR Interferometry (InSAR). Moreover, the system upgrading is also aimed at improving the performances achievable in repeat-pass applications, such as Differential SAR Interferometry, (DInSAR), which require very precise measurement of the tracks described during the flight by the SAR antennas.

In this paper we discuss the extension of an algorithm for efficient processing of SAR data acquired in sliding spotlight mode based on a two-step approach. The two-step spotlight data processing procedure, already introduced in the literature, is a very simple and effective procedure because it is based on a plain use of classical (i.e. stripmap mode) SAR processing codes. The algorithm here proposed extends the two-step approach in such a way t account for the presence of squint. Experiments have been carried out on simulated data to clarify the rationale of the method and to confirm its validity. Results obtained by processing real data of the COSMO-SKYMED constellation are also presented.

Airborne SAR focusing is affected by motion errors corrupting data acquired onboard. In order to account for these errors, MOtion COmpensation (MOCO) algorithms are necessary. However, efficient implementation of such MOCO algorithms requires use of proper approximations in the sensor-to-target distance history, which may impair the accuracy of the final SAR images. To circumvent this problem, some methods, such as the PTA (which stands for Precise Topography- and Aperture- dependent) algorithm, have been recently devised in the literature. This paper discusses limits of the PTA algorithm and provides some modifications aimed at improving its performances.

The differential synthetic aperture radar interferometry (DInSAR) technique has dramatically boosted the application of remote sensing in many geophysical disciplines, particularly tectonics. Coseismic interferograms have provided, in many cases, “images of earthquakes,” showing the surface displacement due to the deep fault dislocation. Aside from being visually appealing, such interferograms are of fundamental importance for the analysis, by means of appropriate dislocation models, of the geometrical and kinematic characteristics of the fault, which are also parameters of key interest for earthquake risk management. This paper provides a contribution in the general framework of the integration of dislocation models in DInSAR processing. In particular, with reference to coseismic interferograms, it proposes a technique that allows the direct inversion of wrapped interferograms for dislocation model analysis. This option makes it possible to avoid the critical and error-prone processing step of phase unwrapping, carried out in the classical analysis of interferometric data. Examples of inversion of real data, relevant to the 1999 Athens and Izmit earthquakes, demonstrate the feasibility and the advantages of this data processing approach.

Synthetic aperture radar (SAR) tomography is a technique that extends the concept of SAR interferometry for the accurate localization and monitoring of ground scatterers. Data that are being acquired by the new high resolution SAR sensors offer new perspectives in the 3-D reconstruction and monitoring of urban areas and, particularly, of individual buildings. SAR tomography allows increasing the density of measurements by handling situations where multiple stable scatterers interfere in the same resolution cell. The detection of reliable, i.e., persistent, scatterers is however a challenging issue. In this paper, we investigate three detection approaches: The first is based on a modification of information theoretical criteria; the last two are based on the generalized likelihood ratio test. Theoretical performances are analyzed in details on simulated data, and results of the application to real data from both medium and very high resolution sensors are also provided.

Layover is frequent in imaging and monitoring with synthetic aperture radar (SAR) areas characterized by a high density of scatterers with steep topography, e.g., in urban environment. Using medium-resolution SAR data tomographic techniques has been proven to be capable of separating multiple scatterers interfering (in layover) in the same pixel. With the advent of the new generation of high-resolution sensors, the layover effect on buildings becomes more evident. In this letter, we exploit the potential of the 4-D imaging applied to a set of TerraSAR-X spotlight acquisitions. Results show that the combination of high-resolution data and advanced coherent processing techniques can lead to impressive reconstruction and monitoring capabilities of the whole 3-D structure of buildings.

COSMO/SKYMED is currently the unique constellation of synthetic aperture radar (SAR) sensors operative, which is also for civilian use. On April 6, 2009, an Mw 6.3 earthquake struck the city of l'Aquila in Central Italy. The constellation acquired data stacks over the hit area at an unprecedented temporal rate. In this letter, the results obtained by processing several data set via two independent multitemporal differential interferometric SAR techniques are presented to demonstrate the capability of this constellation in postseismic deformations monitoring.

Multitemporal differential interferometric synthetic aperture radar analysis is of fundamental importance in the monitoring of Earth surface displacements. In this context, a key role for the reconstruction of the deformation maps and time series is played by the phase unwrapping (PhU) that reconstructs the unrestricted phase signals starting from the measured wrapped versions, i.e., the interferograms. PhU is typically carried out independently for each interferogram in the 2-D azimuth-range domain via the efficient minimum cost flow (MCF) optimization technique. Recently, it has been proposed a two-step (TS) strategy that exploits both the temporal and the spatial structures of the available interferograms. The MCF algorithm is applied in this case also in the temporal/spatial baseline domain, and this step is combined with the classical 2-D space unwrapping. However, the restriction on the use of the MCF algorithm in the baseline domain poses limitations on the interferogram generation scheme. We present a formulation which makes use of the overdetermined nature of the operator that relates the phase differences to the absolute phase values: the problem is addressed in a more general framework that can cope with the 3-D (2-D space and time) nature of the data. This formulation is derived with reference to the sequential (TS) approach to overcome its restrictions on the interferogram generation. The new algorithm is validated on both simulated and real data. Moreover, the use of this new formulation for a full 3-D unwrapping is also addressed.

On April 6th2009 a Mw=6.3 earthquake struck the area around the city of L'Aquila in Italy. SAR systems have been proven to be valuable sensors for analyzing the effect of earthquakes and monitoring post-seismic displacements. Due to the low deformation rate, the study of post-seismic events requires the use of a multi-temporal InSAR approach. COSMO/SKYMED is a constellation of SAR sensors of 4 X-band sensors operative also for the civilian use. Thanks to the availability of a stack of ascending acquisitions, ad hoc programmed by ASI on the area stricken by the earthquake, it was possible to provide post-seismic deformation maps by using two different multi-temporal interferometric approaches: the SPINUA and SBAS techniques. The work is carried out in the framework of the MORFEO project dedicated to the monitoring of the landslides risk by means of Earth Observation data. The displacement maps related to the post-seismic activity are presented and commented. The results clearly show the potentiality of the COSMO/SKYMED constellation use for emergency monitoring.

Differential SAR Interferometry (DInSAR) is a remote sensing technique which allows monitoring ground deformation with accuracy of the order of the transmitted wavelength by exploiting the phase difference (interferogram) of two temporally separated SAR images relevant to the same area. In addition, when more than two multi-pass acquisitions relevant to the same area are available, they can be properly combined by means of recent multitemporal DInSAR algorithms, in order to detect and follow the temporal evolution of ground deformation via the generation of spatially dense time series. Such a multitemporal DInSAR technique is nowadays developed and operative with space-borne SAR data, whereas specific problems may limit its application to airborne data. In this work, starting from the results already shown in previous works and relevant to an X-Band airborne DInSAR experiment carried out over the Perugia area (center of Italy) by using the OrbiSAR system, we carry out a DInSAR multitemporal analysis of data relevant to a 16 km (in azimuth) by 4 km (in range) region.

In the last years MultiDimensional (3D and 4D) Synthetic Aperture Radar (SAR) techniques, also known as SAR tomography and differential SAR tomography, are emerging in the field of coherent combination of multibaseline/multitemporal SAR data. With respect to the classical differential interferometric processing, these techniques improve the capability of detection and monitoring of the ground targets. Moreover they were proven to be effective in resolving the signal interference due to the layover effect, that may occur in areas with high density of scatterers located on vertical structures, such as urban areas. Beside the development of these advanced techniques the new generation of sensor, such as TerraSAR-X and COSMO-SKYMED with very high spatial resolution offer new perspectives in the imaging and monitoring of urban areas. In this paper we address the application of the SAR tomography to real spaceborne data. Particularly, we show and discuss the first results of the application of this technique to high resolution TerraSAR-X data.

Four-dimensional synthetic aperture radar (SAR) imaging, also known as differential SAR tomography, is a new research topic in the framework of coherent multitemporal/multibaseline SAR processing that extends the interferometry concept. Four-dimensional SAR imaging-based processing could improve the capability of ground-scatterer monitoring with respect to classical differential interferometric SAR processing. The first results on the applicability of such an advanced tomographic SAR processing to real spaceborne data were recently discussed in the literature. In this letter, we present the results of an experiment with a data set that demonstrates the potentialities of this new technique for monitoring complex targets, such as infrastructures.

Moon exploitation is among the next space mission priorities. Earth observation (EO), which is traditionally implemented on artificial lower Earth orbit satellites, can be, in principle, extended to the platform constituted by the natural Earth satellite. With this regard, we investigate the features related to the EO by a possible Moon-borne synthetic aperture radar system in terms of imaging characteristics and potential applications, as well as of expected limitations.

Phase unwrapping is a key step in DInSAR stack analysis: it allows restoring the phase values starting from the restricted ones to extract the deformation time series of the observed area. Most of the available interferogram stack phase unwrapping techniques unwrap each interferogram separately. Based on a strategy proposed in the literature, in this work we discuss an unwrapping procedure that exploits both the temporal and spatial characteristics of the interferogram stack. In particular we propose a technique that allows carrying out a temporal unwrapping step with a generic set of interferograms. The validation of our method is carried out by processing simulated data.

Multi-Dimensional (3D/4D) SAR imaging (SAR Tomography and Differential SAR Tomography) allows the localization and monitoring of ground scatterers, even interfering in the same azimuth-range pixel. Indeed, the presence of multiple scatterers has shown to affect even the performances of high resolution radar systems. In this paper we discuss two strategies for the detection of interfering scatterer pairs. The first one is based on the extension of the GLRT test already proposed for the detection of single scatterers, the second one is based on the BIC criteria commonly used in the contest of model order selection. Performances of the two decision schemes are evaluated on simulated data.

Three-dimensional synthetic aperture radar (SAR) imaging, a technique also known as SAR tomography, uses multiple views to extend the capability of SAR systems to 3-D imaging by achieving a profiling of the scattering power at different heights. Multiple views are obtained with the current satellite technology via successive passes of a single antenna SAR sensor over the same scene, but next-generation sensor formations are foreseen to acquire multistatic data. Conventional processing, such as the beamforming, or singular values decomposition inversion is based on geometrical derivations and, hence, assumes the accurate phase calibration and the absence of target decorrelation. This paper analyzes the effects of phase miscalibration due to residual uncompensated atmospheric contribution and temporal decorrelation and proposes a 3-D imaging technique based on a linear minimum mean square error approach. The resulting algorithm extends the possibilities of the conventional processing by carrying out an integration of data that accounts for theaprioridata correlation properties. Hence, it allows handling of the presence of additional stochastic contributions such as: temporal coherence losses and atmospheric phase miscalibration. Moreover, with reference to future bistatic and multistatic systems, it permits an improved coherent integration of data acquired by simultaneous antenna in repeated passes.

The superposition of contributions from different stable targets within the same pixel is a phenomenon that may impair the imaging and monitoring of ground scatterers via the multipass synthetic aperture radar (SAR) interferometry technique. Three-dimensional SAR imaging, also known as SAR tomography, uses multiple views to profile the scattering power at different heights. This technique has been shown to be capable of separating interfering target responses on real data. Differential SAR tomography has been recently proposed as a technique that extends the potentialities of SAR tomography to the target deformation monitoring. It performs a 4-D space-velocity imaging that enables not only separating interfering targets in elevation but also distinguishing their single slow deformation velocities. This work addresses for the first time the application of 4-D SAR imaging to real data to determine the height and mean deformation velocity of single scatterers and double-scattering mechanisms interfering at high resolution in the same pixel. It also discusses the postprocessing steps required to identify the presence of stable single and double scatterers after elevation-velocity focusing. Moreover, it proposes a technique for the extraction of time series from interfering targets to measure possible nonlinear temporal deformations.

Multidimensional synthetic aperture radar (SAR) imaging is a technique based on coherent SAR data combination for space (full 3-D) and space deformation-velocity (4-D) analysis. It is an extension of the concepts of SAR interferometry and differential interferometry SAR and offers new options for the analysis and monitoring of ground scenes. In this paper, we consider the problem of detecting single scatterers for localization and monitoring issues. To this end, we resort to a constant false alarm rate (CFAR) detection scheme which can be synthesized according to three different design criteria: generalized likelihood ratio test, Rao test, and Wald test. At the analysis stage, the performance of the aforementioned detector is compared to that of a previously proposed CFAR scheme, based on the multi-interferogram complex coherence and widely used in persistent scatterer interferometry. The analysis is conducted both on simulated and on real SAR data, acquired by ERS-1/2 satellites. Finally, Cramer-Rao lower bounds for the estimation of the scatterer elevation and velocity are provided.

This work is focused on the detection of single and multiple scatterers in multiview/multitemporal SAR data in order to locate and monitor a high number of ground structures with low signal misinterpretation. This issue is addressed here by combining amplitude and phase data, differently from common techniques for the detection of single scatterers which rely on phase coherence measures. Experiments with real satellite C-band data are presented with both full resolution and multilook processing.

4D (space-velocity) SAR focusing is applied to real data acquired over urban areas to determine the position, in 3D, and the deformation velocity of single and double scatterers interfering, at high resolution, in the same azimuth-range pixel. We discuss the procedure required to identify the presence of stable single and double scatterers after the elevation-velocity focusing. Moreover we present a technique for the separation of time series associated with interfering scatterers to measure their possible non linear temporal deformations.

Differential synthetic aperture radar interferometry (DInSAR) is a remote sensing technique that allows monitoring ground deformation with accuracy of the order of fractions of the radiated wavelength, by means of proper combination and processing of repeat-pass data. In contrast to the satellite case, application of such a technique to airborne data is not, today, a well-established task. Several airborne campaigns, involving mainly C/L-band data, have been planned in the last years to exploit the potentialities of these more flexible platforms for deformation monitoring. In this paper, we show the results of an airborne DInSAR X-band experiment carried out over the Perugia area (center of Italy) by using the OrbiSAR system. We discuss the processing chain applied to the acquired data, which allows achieving a satisfactory compromise between accuracy and efficiency. Eleven repeated passes were carried out in two days; two corner reflectors were located on the ground in a hilly region. One corner reflector was vertically moved between the two days to evaluate the system detection capability. Moreover, we carry out an analysis of all possible differential interferograms for a region 2 4 km wide.

In this work we describe the application of the basic small BAseline subset (SBAS) technique, which exploits multilook interferograms, to a number of active volcanic areas. The use of such a technique reduces the amount of data to be processed and simplifies the analysis of geophysical phenomena occurring in extended areas (up to 100 km by 100 km). Moreover, it can be trivially extended in order to combine data acquired by different sensors with similar geometrical and electromagnetic characteristics, i.e., ERS and ENVISAT IS-2 mode, thus allowing an easy extension of the temporal observation window. The selected test sites for this study are Long Valley caldera, Mt. Etna and the Neapolitan Volcanic district (Mt. Vesuvio and Campi Flegrei caldera). Finally, we shortly analyze the implications of the use of forthcoming SAR sensors that operates in L-and X-bands.

We have investigated the deformation affecting the Campi Flegrei caldera (Italy), from 2002 to the end of 2006, by analyzing ENVISAT ASAR IS-2 data. This study has been performed by exploiting the SBAS-DInSAR algorithm that allows us to detect earth surface displacements and to investigate their temporal evolution via the generation of deformation time series. The presented analysis highlighted the renewed volcanic activity that started on mid-2005; moreover, we have combined the ascending and descending data in order to separate the vertical and east-west components of the detected displacements. The obtained results have been confirmed by the leveling data collected by the Osservatorio Vesuviano.

Multi-Dimensional (MultiD) SAR imaging is a modern technique, based on coherent SAR data combination, aimed to space (full-3D) and space deformation-velocity (4D) analysis. It extends the concept of SAR interferometry and differential interferometry and offers new options for the analysis and monitoring of ground scenes. With this regard, we discuss the current status and the results obtained by processing ERS real data, we investigate perspectives related to the next generation multi-static satellite formations, and we show some sample results regarding 3D and 4D theoretical performance bounds.

Enhanced spatial differences (ESD) is a new processing chain for monitoring ground deformations at small scale over wide areas. Core of the processing is the spatial differencing (SD) step that performs a quick preliminary estimation of the mean deformation velocity and residual topography via spatial differences. We show the results achieved by applying the ESD algorithm to data collected over adjacent tracks for ERS and ENVISAT.

In this paper we show the results of an airborne differential SAR interferometry (DInSAR) experiment carried out over the Perugia area, center of Italy, by using the X-Band OrbiSAR system. Measurements on corner reflectors allowed us evaluating the system detection capability.

This work provides a geometrical analysis to assess the effects of center-beam approximation, crucial for efficient airborne raw data focusing, on the final image.

Microwave scattering is a rather complex mechanism, especially in urban areas. Three-dimensional (3-D) synthetic aperture radar (SAR) tomography is a technique that uses multiple views to map the scattering power at different heights, thus extending the capability of SAR sensors to fully image the scene in the 3-D space. This paper presents a first validation of spaceborne long-term SAR tomography by demonstrating the capability to resolve a simple layover case, i.e., to separate single- and double-scattering mechanisms within imaged pixels. Results obtained with real data acquired by the European Remote Sensing 1 and 2 (ERS-1 and ERS-2) satellites over the urban area of Napoli are presented. As an additional contribution, an innovative algorithm estimating residual topography and surface deformation, called the spatial-differencing technique, is also discussed in detail at the data calibration stage

Accurate subpixel registration of synthetic aperture radar (SAR) images is an issue that is again growing interest since its initial developments related to two-pass interferometry. Recent progress in coherent (multichannel) SAR processing raises the need for accurate registration of data takes acquired with large baseline spans, high temporal coverage, and with different frequency and/or operational modes. In this paper, we discuss a SAR image-registration procedure, based on the use of external measures which allows obtaining a very accurate alignment of SAR images. The presented technique makes use of a digital elevation model and of the precise information about the acquisition flight tracks, to compute the warping functions that map the position of each pixel in the different takes, thus avoiding any approximation. The resulting algorithm is simple, robust, precise, and very efficient; as a matter of fact, it may achieve high accuracy even in critical areas, such as steep topography regions. Moreover, the availability of an analytical and exact model allows performing a detailed sensitivity analysis that can be useful in evaluating the applicability of this technique even to future high-precision satellite systems. Extensive testing, carried out on several real European Remote Sensing and ENVISAT datasets, clearly shows the effectiveness of such algorithm in registering critical SAR images

Synthetic aperture radar (SAR) interferometry is a modern efficient technique that allows reconstructing the height profile of the observed scene. However, apart for the presence of critical nonlinear inversion steps, particularly crucial in abrupt topography scenarios, it does not allow one to separate different scattering mechanisms in the elevation (height) direction within the ground pixel. Overlay of scattering at different elevations in the same azimuth-range resolution cell can be due either to the penetration of the radiation below the surface or to perspective ambiguities caused by the side-looking geometry. Multibaseline three-dimensional (3-D) SAR focusing allows overcoming such a limitation and has thus raised great interest in the recent research. First results with real data have been only obtained in the laboratory and with airborne systems, or with limited time-span and spatial-coverage spaceborne data. This work presents a novel approach for the tomographic processing of European Remote Sensing satellite (ERS) real data for extended scenes and long time span. Besides facing problems common to the airborne case, such as the nonuniformly spaced passes, this processing requires tackling additional difficulties specific to the spaceborne case, in particular a space-varying phase calibration of the data due to atmospheric variations and possible scene deformations occurring for years-long temporal spans. First results are presented that confirm the capability of ERS multipass tomography to resolve multiple targets within the same azimuth-range cell and to map the 3-D scattering properties of the illuminated scene.

This work addresses the derivation of the phase difference-based maximum likelihood (ML) phase unwrapping algorithm. To this end, we derive the joint statistics of the phase differences on a two-dimensional grid for the multichannel case, where several scaled wrapped phase values are available. Subsequently, we determine and study the structure of the phase difference-based ML estimator and compare it to known phase unwrapping techniques. This work allows us to frame single and multichannel algorithms in a common formulation. Moreover, among the known single-channel phase difference-based procedures, we identify those attaining an ML solution. We also show that multichannel phase difference-based and, recently proposed, phase-based ML algorithms achieve equivalent solutions.

The Small BAseline Subset (SBAS) approach is a differential synthetic aperture radar interferometry (DIFSAR) technique that allows analyzing deformation phenomena affecting both extended area and localized structures, by exploiting the phase difference of SAR image pairs characterized by small baselines. In this work we process a large set of ERS-1/2 data, acquired from ascending and descending orbits, at both small and large scale resolution and extend the obtained time series with available ENVISAT acquisitions. The results, relevant to the Napoli Bay area (Italy), are compared with geodetic and GPS data in order to achieve a quantitative analysis of the SABS algorithm performances

We discuss the role of processing geometry and the problem of motion compensation for non zero squint in airborne SAR processing.

In this work we present the results of an airborne differential interferometry experiment carried out by using the ORBISAR X-band system. Use of a high track measurement accuracy allowed us to fulfill the requirements of Fornaro et al. (2003), where repeat pass phase accuracy has been quantified in terms of position measurement errors. The presented experiment can be considered a first step towards the development of operative airborne differential interferometry for accurate ground deformation monitoring.

This paper presents the first results of a multibaseline SAR experiments for the reconstruction of the 3D back-scattering properties of ground scenes by using ERS data

This paper presents a DIFSAR approach that allows us to detect and follow the temporal evolution of surface deformations at different spatial scales. In particular, our solution extends the capability of the algorithm referred to as small baseline subsets (SBAS) technique (Berardino et al., 2002), and allows us to investigate large scale deformation phenomena as well as displacements of single buildings or structures. The proposed technique relies on small baseline DIFSAR interferograms only, in order to mitigate the decorrelation phenomena, and requires two different sets of data generated at low (multi-look) and high (single-look) spatial resolution, respectively. The algorithm has been tested with the data acquired by the European Remote Sensing (ERS) satellites which are relative to the city of Napoli (Italy) and surroundings; the results have been validated by using geodetic data.

We propose a new approach for monitoring the evolution of Earth surface deformations via differential SAR interferometry. It allows us to overcome the limitations of standard techniques by incorporating the knowledge of the deformations associated to tie points and available spatial deformation models.

This work addresses the derivation of a phase-difference (gradient) based maximum likelihood (ML) phase unwrapping algorithm. In particular, we determine and study the structure of the ML phase unwrapping on a 2D grid in the multi-channel case and compare it with existing phase unwrapping algorithms. This allows us first to frame single-channel, phase based phase unwrapping algorithm in a general formulation. Second, among the known single-channel, phase-difference based phase unwrapping algorithms we identify those achieving a ML solution. Although achieving results similar to existing phase-based ML phase unwrapping algorithm in the multi-channel case, our approach allows to easily incorporate possible a priori knowledge about the absolute phase variation dynamics.

We study the effects of residual uncompensated trajectory deviations on the phase accuracy of motion compensated SAR images. We show that linear and quadratic deviations interact with the SAR processing and generate additional phase artifacts with respect to what is expected by simple geometric considerations.

MINERVA (Monitoring by Interferometric SAR of Environmental Risk in Volcanic Areas) is a small scale service demonstration project financed by ESA in the Data User Programme framework. The objective of the project is the design, development and assessment of a demonstrative information service based on the interferometric processing of images from the ASAR instruments on board ERS1/2 and ENVISAT-I. The system is based on a new approach for the processing of INSAR data, which allows to optimize the quality of interferograms spanning from 35 days up to several years, and to merge them to generate a single solution describing the temporal evolution of the ground deformations in the examined risk area. The system allows to update this solution each time a new SAR image is available, and constitutes therefore an innovative tool for monitoring of the ground displacements in risk areas.

Deals with the use of multipass synthetic aperture radar (SAR) data in order to achieve three-dimensional tomography reconstruction in presence of volumetric scattering. Starting from azimuth- and range-focused SAR data relative to the same area, neglecting any mutual interaction between the targets, and assuming the propagation in homogeneous media, we investigate the possibility to focus the data also in the elevation direction. The problem is formulated in the framework of linear inverse problem and the solution makes use of the singular value decomposition of the relevant operator. This allows us to properly take into account nonuniform orbit separation and to exploit a priori knowledge regarding the size of the volume interested by the scattering mechanism, thus leading to superresolution in the elevation direction. Results obtained on simulated data demonstrate the feasibility of the proposed processing technique.

We present results obtained via an innovative spaceborne SAR interferometry algorithm showing that, despite its quiescent stage, the Somma-Vesuvius volcanic complex is subject to a particular deformation process. This is characterized by a rather continuous subsidence effect, revealed by both ERS satellite data and levelling surveys, between 1992 and 2000. These deformations are mainly localized in two zones involving the Vesuvius cone and a narrow discontinuous annular area that extends around the base of the Somma edifice. A likely explanation of subsidence at both sites involves the joint effect of gravitational sliding and extensional tectonic stress occurring at the contact between different lithological units.

In the area of tomographic synthetic aperture radar processing we present a new technique that makes use of the singular value decomposition method to improve the resolution limits by including a-priori information about the radiation penetration depth.

Multiple SAR data sets can be exploited to improve the system range resolution. Obtainable resolution improvement can be impaired by a coherence loss among the different data acquisitions. The effect of different decorrelation factors on the attainable resolution is investigated by numerical simulation.

We present a new differential synthetic aperture radar (SAR) interferometry algorithm for monitoring the temporal evolution of surface deformations. The presented technique is based on an appropriate combination of differential interferograms produced by data pairs characterized by a small orbital separation (baseline) in order to limit the spatial decorrelation phenomena. The application of the singular value decomposition method allows us to easily "link" independent SAR acquisition datasets, separated by large baselines, thus increasing the observation temporal sampling rate. The availability of both spatial and temporal information in the processed data is used to identify and filter out atmospheric phase artifacts. We present results obtained on the data acquired from 1992 to 2000 by the European Remote Sensing satellites and relative to the Campi Flegrei caldera and to the city of Naples, Italy, that demonstrate the capability of the proposed approach to follow the dynamics of the detected deformations.

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 authors present a new spotlight SAR data-focusing algorithm based on a two-step processing strategy that combines the advantages of two commonly adopted processing approaches: the efficiency of SPECAN algorithms and the precision of stripmap focusing techniques. The first step of the proposed algorithm implements a linear and space-invariant azimuth filtering that is carried out via a deramping-based technique representing a simplified version of the SPECAN approach. This operation allows the authors to perform a bulk azimuth raw data compression and to achieve a pixel spacing smaller than (or equal to) the expected azimuth resolution of the fully focused image. Thus, the azimuth spectral folding phenomenon, typically affecting the spotlight data, is overcome, and the space-variant characteristics of the stripmap system transfer function are preserved. Accordingly, the residual and precise focusing of the SAR data is achieved by applying a conventional stripmap processing procedure requiring a minor modification and implemented in the frequency domain. The extension of the proposed technique to the case of high bandwidth transmitted chirp signals is also discussed. Experiments carried out on real and simulated data confirm the validity of the presented approach, which is mainly focused on spaceborne systems.

This paper presents a new two-dimensional (2-D) phase unwrapping (PhU) algorithm based on a least squares (LS) region growing strategy: the wrapped phase image is partitioned in different regions that are sequentially unwrapped via a LS algorithm. Reliable regions are dealt with at the beginning of the procedure, while critical areas are unwrapped in the final steps, thus avoiding error propagation from critical to reliable areas. A conditioned least squares formulation of the phase unwrapping problem is the core of the proposed procedure: this allows the solution to be tied to "some" known boundary phase values, thus guaranteeing the correct joining of the reconstructed phase in between the different regions and preventing them from being independently unwrapped. The application of the finite element method allows a straightforward implementation of the algorithm in the discrete domain case. Experimental results, carried out on simulated and real interferometric SAR data, show the effectiveness of the proposed algorithm and the improved performances with respect to existing unwrapping procedures.

This paper is concerned about the generation of interferometric phase patterns using synthetic aperture radar (SAR) images obtained by processing the raw data and reference function both quantized at one bit (Signum Coded). Such processing technique involves one-bit coded (i.e., binary) sequences, and can be efficiently implemented in real time using very simple and low cost hardware. It is shown that the proposed SC processing technique preserves, besides the image intensities, also interferometric phase patterns, before and after phase unwrapping. To test the performance of the proposed technique, experiments have been carried out on real data relative to the ERS-1 mission. Quantitative comparison between the results of conventional and SC processing clearly show that the presented method can be used for quick-look DEMs generation. Moreover, in accordance with the SC-SAR theory, an upsampling has also been performed on the signals to be processed to obtain higher quality patterns. This produce a noticeable improvement of the obtained results, so that the SC techniques can be considered a valid alternative to the conventional ones, still preserving the advantages in terms of real time.

Efficient and precise compensation of the range cell migration (RCM) effect is a key point for a fast and accurate synthetic aperture radar (SAR) data processor. In particular the range-dependent nature of the range cell migration effect complicates the compensation operation. It has been recently shown that an exact compensation of the range-dependent RCM (RDRCM) phenomenon can be carried out either by applying the chirp scaling algorithm or the chirp z-transform procedure. This paper investigates the relationship between the two methods. In particular, it is shown that the chirp z-transform based approach represents a particular implementation of the chirp scaling algorithm. A final discussion is dedicated to show how the chirp z-transform and the chirp scaling procedure can be applied within a SAR data processing algorithm.

Any method that permits retrieving full range (unwrapped) phase values starting from their (-/spl pi/,/spl pi/) determination (wrapped phase) can be defined as a phase unwrapping technique. This paper addresses a new procedure for phase unwrapping especially designed for interferometric synthetic aperture radar applications. The proposed algorithm is based on use of Green's first identity. Results on simulated as well as on real data are presented. They both confirm the excellent performance of the procedure.

The authors exploit the interferometric multifrequency potentiality of the SIR-C/X-SAR system which is equipped with an L-, C-, and X-band sensor. They present a solution to improve the unwrapping performance of the C- and X-band data by considering the L-band unwrapped pattern. A new algorithm for the generation of a single digital elevation model (DEM) combining L-, C-, and X-band information is presented. This solution is based on the fusion of the unwrapped phase patterns by using a Kalman filter. The proposed fusion operation also accounts for the coherence characteristics of the three data sets. The selected test site is the Mt. Etna region in Italy which is very interesting from the volcanological and geological point of view. Numerical assessments of the achieved results are provided by evaluating the height accuracy with respect to a reference DEM.

Repeat-pass interferometry data were acquired during the first and second SIR-C/X-SAR missions in April and October 1994. This paper presents the first results from X-SAR interferometry at four different sites. The temporal separations were one day and six months. At two sites the coherence requirements were met, resulting in high quality interferograms. A digital elevation model in ground range geometry has been derived. The limitations of the X-SAR interferometry are discussed.>