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A geometrical decorrelation constitutes one of the sources of noise present in Synthetic Aperture Radar (SAR) interferograms. It comes from the different incidence angles of the two images used to form the interferograms, which cause a spectral (frequency) shift between them. A geometrical decorrelation must be compensated by a specific filtering technique known as range filtering, the goal of which is to estimate this spectral displacement and retain only the common parts of the images' spectra, reducing the noise and improving the quality of the interferograms. Multiple range filters have been proposed in the literature. The most widely used methods are an adaptive filter approach, which estimates the spectral shift directly from the data; a method based on orbital information, which assumes a constant-slope (or flat) terrain; and slope-adaptive algorithms, which consider both orbital information and auxiliary topographic data. Their advantages and limitations are analyzed in this manuscript and, additionally, a new, more refined approach is proposed. Its goal is to enhance the filtering process by automatically adapting the filter to all types of surface variations using a multi-scale strategy. A pair of RADARSAT-2 images that mapped the mountainous area around the Etna volcano (Italy) are used for the study. The results show that filtering accuracy is improved with the new method including the steepest areas and vegetation-covered regions in which the performance of the original methods is limited. [ABSTRACT FROM AUTHOR]

The use of polarimetric synthetic aperture radar (SAR) data can improve the performance of persistent scatterer interferometry (PSI). However, its huge potential remains locked for the amplitude information-based offset tracking (OT) technology. For example, to the best knowledge of the authors, there is no single example of a polarization-based image optimization method that has been developed for OT processing. In this article, an amplitude contrast enhancement (ACE) algorithm is introduced, which demonstrates the potential of the polarimetric SAR data on the improvement of OT performance. Its core idea is finding the optimal combination of the different scattering mechanisms for each pixel to improve the contrast. First, the orientation of the reflected polarization ellipse is removed, to avoid the influence of the geometric relationship between the antenna and the target, and the properties of the target. Then three similarity parameters are defined to represent the three basic reflection types of the single bounce, the double bounce, and the random reflection. After that, the optimizing equation is constructed with two optimizing vectors. Finally, the optimizing vectors are calculated to obtain the enhanced amplitude image. Three examples of the enhancement are presented with different PolSAR images sets of both full- (Radarsat-2) and dual-polarization (TerraSAR-X and Sentinel-1). The performance of ACE-OT has been compared with another method, the adaptive histogram enhancement (AHE). The impact of the number of polarization channels available on ACE-OT performance has also been studied. [ABSTRACT FROM AUTHOR]

Pixel selection is a crucial step of all advanced Differential Interferometric Synthetic Aperture Radar (DInSAR) techniques that have a direct impact on the quality of the final DInSAR products. In this paper, a full-resolution phase quality estimator, i.e., the temporal phase coherence (TPC), is proposed for DInSAR pixel selection. The method is able to work with both distributed scatterers (DSs) and permanent scatterers (PSs). The influence of different neighboring window sizes and types of interferograms combinations [both the single-master (SM) and the multi-master (MM)] on TPC has been studied. The relationship between TPC and phase standard deviation (STD) of the selected pixels has also been derived. Together with the classical coherence and amplitude dispersion methods, the TPC pixel selection algorithm has been tested on 37 VV polarization Radarsat-2 images of Barcelona Airport. Results show the feasibility and effectiveness of TPC pixel selection algorithm. Besides obvious improvements in the number of selected pixels, the new method shows some other advantages comparing with the other classical two. The proposed pixel selection algorithm, which presents an affordable computational cost, is easy to be implemented and incorporated into any advanced DInSAR processing chain for high-quality pixels’ identification. [ABSTRACT FROM AUTHOR]

The rationale of polarimetric optimization techniques is to enhance the phase quality of the interferograms by combining adequately the different polarization channels available to produce an improved one. Different approaches have been proposed for polarimetric persistent scatterer interferometry (PolPSI). They range from the simple and computationally efficient BEST, where, for each pixel, the polarimetric channel with the best response in terms of phase quality is selected, to those with high-computational burden like the equal scattering mechanism (ESM) and the suboptimum scattering mechanism (SOM). BEST is fast and simple, but it does not fully exploit the potentials of polarimetry. On the other side, ESM explores all the space of solutions and finds the optimal one but with a very high-computational burden. A new PolPSI algorithm, named coherency matrix decomposition-based PolPSI (CMD-PolPSI), is proposed to achieve a compromise between phase optimization and computational cost. Its core idea is utilizing the polarimetric synthetic aperture radar (PolSAR) coherency matrix decomposition to determine the optimal polarization channel for each pixel. Three different PolSAR image sets of both full- (Barcelona) and dual-polarization (Murcia and Mexico City) are used to evaluate the performance of CMD-PolPSI. The results show that CMD-PolPSI presents better optimization results than the BEST method by using either $D_{\mathrm{ A}}$ or temporal mean coherence as phase quality metrics. Compared with the ESM algorithm, CMD-PolPSI is 255 times faster but its performance is not optimal. The influence of the number of available polarization channels and pixel’s resolutions on the CMD-PolPSI performance is also discussed. [ABSTRACT FROM AUTHOR]

Speckle noise and decorrelation can hamper the application and interpretation of PolSAR images. In this paper, a new adaptive multitemporal Pol(DIn)SAR filtering and phase optimization algorithm is proposed to address these limitations. This algorithm first categorizes and adaptively filters permanent scatterer (PS) and distributed scatterer (DS) pixels according to their polarimetric scattering mechanisms [i.e., the scattering-mechanism-based filtering (SMF)]. Then, two different polarimetric DInSAR (POLDInSAR) phase OPTimization methods are applied separately on the filtered PS and DS pixels (i.e., POLOPT). Finally, an inclusive pixel selection approach is used to identify high-quality pixels for ground deformation estimation. Thirty-one full-polarization Radarsat-2 SAR images over Barcelona (Spain) and 31 dual-polarization TerraSAR-X images over Murcia (Spain) have been used to evaluate the performance of the proposed algorithm. The PolSAR filtering results show that the speckle of PolSAR images has been well reduced with the preservation of details by the proposed SMF. The obtained ground deformation monitoring results have shown significant improvements, about $\times 7.2$ (the full-polarization case) and $\times 3.8$ (the dual-polarization case) with respect to the classical full-resolution single-pol amplitude dispersion method, on the valid pixels’ densities. The excellent PolSAR filtering and ground deformation monitoring results achieved by the adaptive Pol(DIn)SAR filtering and phase optimization algorithm (i.e., the SMF-POLOPT) have validated the effectiveness of this proposed scheme. [ABSTRACT FROM AUTHOR]

Mitigating the atmospheric phase delay is one of the largest challenges faced by the differential synthetic aperture radar (SAR) interferometry community. Recently, many publications have studied correcting the stratified tropospheric phase delay by assuming a linear model between them and the topography. However, most of these studies have not considered the effect of turbulent atmospheric artifacts when adjusting the linear model to data. In this paper, we present an improved technique that minimizes the influence of the turbulent atmosphere in the model adjustment. In the proposed algorithm, the model is adjusted to the phase differences of pixels instead of using the unwrapped phase of each pixel. In addition, the different phase differences are weighted as a function of its atmospheric phase screen covariance estimated from an empirical variogram to reduce, in the model adjustment, the impact of pixel pairs with a significant turbulent atmosphere. The good performance of the proposed method has been validated with both the simulated and real Sentinel-1A SAR data in the mountainous area of Tenerife island, Spain. [ABSTRACT FROM AUTHOR]

This paper presents a comparative study among four operational detectors that work by automatically post-processing synthetic aperture radar (SAR) images acquired from the satellite platforms RADARSAT-2 and COSMO-SkyMed. Challenging maritime scenarios have been chosen to assess the detectors’ performance against features such as ambiguities, significant sea clutter, or irregular shorelines. The SAR images which form the test data are complemented with ground truth to define the reference detection configuration, which permits quantifying the probability of detection, the false alarm rate, and the accuracy of estimating ship dimensions. Although the results show that all the detectors perform well, there is no perfect detector, and a better detection system could be developed that combines the best elements from each of the single detectors. In addition to the comparison exercise, the study has facilitated the improvement of the detectors by highlighting weaknesses and providing means for fixing them. [ABSTRACT FROM PUBLISHER]

Ground-based synthetic aperture radar (SAR) (GB-SAR) sensors represent an effective solution for the monitoring of ground displacement episodes. Initially, the most GB-SAR sensors were based on vector network analyzers (VNA). This type of solution, characterized by a slow scanning time comparable to the decorrelation of the troposphere medium, compromised in many cases the quality of final products for the application of persistent scatterer interferomerty (PSI) techniques. The development of GB-SAR sensors based on the use of stepped linear frequency modulated continuous wave (SLFMCW) signals has led to significant improvements during the last years. They have allowed fulfilling the need of temporal homogeneity of the troposphere during the acquisition time and, moreover, they have favored the acquisition of reliable polarimetric SAR (PolSAR) measurements without drastically increasing the scanning time. This fact has boosted the inclusion of polarimetric SAR interferometry (PolInSAR) algorithms in PSI processing chains, which are demonstrating to outperform classical single-polarimetric performances. The objective of this paper is twofold. On the one hand, a general overview of the polarimetric RiskSAR sensor, developed by the Universitat Politècnica de Catalunya (UPC), is put forward as an example of SLFMCW GB-SAR system implementation. On the other hand, a complete theoretical description of ground-based SAR (GB-SAR) interferometry (GB-InSAR) techniques for PSI purposes is widely discussed. The adaptation of the Coherent Pixels Technique to obtain the linear and nonlinear components of ground displacement phenomena is proposed. In the second part of this paper, the displacement maps and time series over two very different scenarios are presented in order to show the feasibility of GB-SAR sensors for terrain displacement monitoring applications. [ABSTRACT FROM PUBLISHER]

Urban subsidence and landslides are among the greatest hazards for people and infrastructure safety and they require an especial attention to reduce their associated risks. In this framework, ground-based synthetic aperture radar (SAR) interferometry (GB-InSAR) represents a cost-effective solution for the precise monitoring of displacements. This work presents the application of GB-InSAR techniques, particularly with the RiskSAR sensor and its processing chain developed by the Remote Sensing Laboratory (RSLab) of the Universitat Politècnica de Catalunya (UPC), for the monitoring of two different types of ground displacement. An example of urban subsidence monitoring over the village of Sallent, northeastern of Spain, and an example of landslide monitoring in El Forn de Canillo, located in the Andorran Pyrenees, are presented. In this framework, the key processing particularities for each case are deeply analyzed and discussed. The linear displacement maps and time series for both scenarios are showed and compared with in-field data. For the study, fully polarimetric data acquired at X-band with a zero-baseline configuration are employed in both scenarios. The displacement results obtained demonstrate the capabilities of GB-SAR sensors for the precise monitoring of ground displacement phenomena. [ABSTRACT FROM PUBLISHER]

The application of differential synthetic aperture radar interferometry (DInSAR) techniques has been traditionally limited to the single-polarimetric case. The launch of satellites with polarimetric capabilities has triggered the synergy between polarimetric and interferometric algorithms, leading to a significant improvement in final DInSAR products. During the last years, the different polarimetric optimization techniques available have been successfully applied to the so-called classical phase quality estimators, i.e., the coherence and the amplitude dispersion estimators. In this context, a new estimator to evaluate the pixels' phase quality, referred to as temporal sublook coherence (TSC), has recently demonstrated to provide promising results in DInSAR applications. The nature of this estimator, which is based on exploiting the spectral properties of pointlike scatterers through the coherence evaluation of different sublooks of the image spectrum, allows its adaptation to the existing polarimetric optimization methods. This letter presents the benefits of extending the TSC estimator to work with fully polarimetric data. For this purpose, a fully polarimetric data set consisting of ten X-band ground-based SAR (GB-SAR) images is employed. The final DInSAR results obtained by means of TSC polarimetric optimization are compared with the ones obtained with its classical single-polarimetric approach, achieving up to more than a twofold increase in the pixels' density. [ABSTRACT FROM PUBLISHER]

Prior to the application of any persistent scatterer interferometry (PSI) technique for the monitoring of terrain displacement phenomena, an adequate pixel selection must be carried out in order to prevent the inclusion of noisy pixels in the processing. The rationale is to detect the so-called persistent scatterers, which are characterized by preserving their phase quality along the multi-temporal set of synthetic aperture radar (SAR) images available. Two criteria are mainly available for the estimation of pixels' phase quality, i.e., the coherence stability and the amplitude dispersion or permanent scatterers (PS) approach. The coherence stability method allows an accurate estimation of the phase statistics, even when a reduced number of SAR acquisitions is available. Unfortunately, it requires the multi-looking of data during the coherence estimation, leading to a spatial resolution loss in the final results. In contrast, the PS approach works at full-resolution, but it demands a larger number of SAR images to be reliable, typically more than 20. There is hence a clear limitation when a full-resolution PSI processing is to be carried out and the number of acquisitions available is small. In this context, a novel pixel selection method based on exploiting the spectral properties of point-like scatterers, referred to as temporal sublook coherence (TSC), has been recently proposed. This paper seeks to demonstrate the advantages of employing PSI techniques by means of TSC on both orbital and ground-based SAR (GB-SAR) data when the number of images available is small (10 images in the work presented). The displacement maps retrieved through the proposed technique are compared, in terms of pixel density and phase quality, with traditional criteria. Two X-band datasets composed of 10 sliding spotlight TerraSAR-X images and 10 GB-SAR images, respectively, over the landslide of El Forn de Canillo (Andorran Pyrenees), are employed for this study. For both datasets, the TSC technique has showed an excellent performance compared with traditional techniques, achieving up to a four-fold increase in the number of persistent scatters detected, compared with the coherence stability approach, and a similar density compared with the PS approach, but free of outliers. [ABSTRACT FROM AUTHOR]

The reliability of any final differential synthetic aperture radar (SAR) interferometry (DInSAR) product is directly related to the phase quality of the interferograms involved in the processing. Performing an appropriate selection of high-quality pixels is hence mandatory in order to avoid the inclusion of noisy data in the processing and thus obtain reliable deformation information within the area of study. In this framework, a new full-resolution pixel selection method based on exploiting the spectral properties of pointlike scatterers is presented. The method is developed from the concept of the so-called coherent scatterers, which are characterized by having a correlated spectrum in a single acquisition, but now involving the temporal axis in the detection. Using the spectral properties of scatterers to perform the DInSAR pixel selection step presents some advantages with respect to the well-known permanent scatterer (PS) approach. On the one hand, the radiometric calibration of data is not required since the detection is now not dependent on the amplitude behavior of scatterers. On the other hand, a reliable pixel selection can be performed even with a reduced number of images due to the nature of the estimator. In contrast, its main limitation relies on the loss of range resolution involved in the sublook generation process. The method is more suited for urban scenarios where the density of temporally stable pointlike scatterers is generally higher. In this context, the final deformation maps obtained using the new method presented are compared, in terms of density and phase quality, with the ones obtained with the well-known traditional PS approach, showing a similar performance. Finally, since both methods characterize pointlike scatterers from different points of view, the combination of both techniques is proposed leading to a significant increase in the pixels' density and giving place to a meaningful improvement in the final DInSAR results. [ABSTRACT FROM PUBLISHER]

This paper presents a new graphical processing technique for fast computation of PO surface integral. In contrast with the original graphical processing approach introduced by the authors in 1993, the new one combines a novel shadowing computation algorithm together with the conventional facet-based Gordon's formula, instead of the pixel-based Asvestas' approximation. The resulting hybrid approach needs more CPU power for very complex radar targets, but is free from the pixel discretization noise inherent to graphical processing. It has the same accuracy as conventional Physical Optics computation, but shadowed facets detection is more than 10 times faster than with the most efficient alternative algorithms of \cal O(N\log N) computational cost. [ABSTRACT FROM PUBLISHER]

In this paper, a study of polarimetric optimization techniques in the frame of differential synthetic aperture radar (SAR) interferometry (DInSAR) is considered. Historically, DInSAR techniques have been limited to the single-polarimetric case, mainly due to the unavailability of fully polarimetric data. Lately, the launch of satellites with polarimetric capabilities, such as the Advanced Land Observing Satellite (ALOS), RADARSAT-2, or TerraSAR-X, allowed merging polarimetric and interferometric techniques to improve the pixels' phase quality and, thus, the density and the reliability of the final DInSAR results. The relationship between the polarimetrically optimized coherence or amplitude dispersion maps and the final DInSAR results is carefully analyzed, using both orbital and ground-based SAR fully polarimetric data. DInSAR processing using polarimetric optimization techniques in the pixel selection process is compared with the classical single-polarimetric approach, achieving up to a threefold increase of the number of pixel candidates in the coherence case and up to a factor of seven in the amplitude dispersion case. [ABSTRACT FROM AUTHOR]

In this paper, a new model-based technique for the compensation of severe height-dependent atmospheric artifacts, using ground-based synthetic aperture radar (SAR) data over mountainous regions, is proposed. The method presented represents an extension of already existing techniques, but now taking into account the effect of steep topography in the atmospheric phase screen compensation process. In addition, the technique is adapted to work with polarimetric SAR data, showing, in that case, a noticeable improvement in the compensation process. The method is validated in the mountainous environment of El Forn de Canillo, located in the Andorran Pyrenees, where there is a slow-moving landslide that nowadays is being reactivated coinciding with strong rain episodes. In this framework, ten zero-baseline fully polarimetric data sets have been acquired at X-band during a one-year measurement campaign (October 2010-October 2011) with the GB-SAR sensor developed at the Universitat Politècnica de Catalunya. First, the impact of the severe atmospheric fluctuations among multitemporal GB-SAR measurements is carefully studied and analyzed. Hence, the need to correctly estimate and compensate the resulting phase differences when retrieving interferometric information is put forward in the frame of differential-SAR-interferometry applications. [ABSTRACT FROM AUTHOR]

Synthetic aperture radar (SAR) systems are inherently band limited in both range and azimuth, and hence, the point spread function (PSF) has the shape of a bidimensional sinc function. In addition, all SAR images are slightly oversampled, and as a consequence, the contribution of a single target extends to more than a single cell. The main lobe and the side lobes of strong scatterers are sometimes clearly visible in the images. This characteristic of the SAR images must be considered when applying differential interferometric synthetic aperture radar (DInSAR) pixel selection algorithms. For persistent scatterers, the properties, for instance, the amplitude stability, are preserved in both redundant information around the main lobe and side lobes. For this reason, a cluster of pixels rather than just the pixel position corresponding to the exact location of the target will be detected. Spatially variant apodization (SVA) is a nonlinear filter based on cosine-on-pedestal weighting functions able to achieve a total side-lobe cancelation without degrading the original image resolution. When working with complex data under complex scattering scenarios, the PSF moves away from the ideal bidimensional sinc, and the SVA performance worsens. The amplitude and phase of the original images could be distorted by the SVA filtering compromising the pixel selection and the quality of the final DInSAR results. In this letter, SVA is used to method locate in the image the side lobes of high-power scatterers and generate a mask while preserving the amplitude and phase of the original images. [ABSTRACT FROM PUBLISHER]

This paper describes a pair of compact CW/FM airborne SAR systems for small UAV-based operation (wingspan of 3.5 m) for low-cost testing of innovative SAR concepts. Two different SAR instruments, using the C and X bands, have been developed in the context of the ARBRES project, each of them achieving a payload weight below 5 Kg and a volume of 13.5 dm3 (sensor and controller). Every system has a dual receiving channel which allows operation in interferometric or polarimetric modes. Planar printed array antennas are used in both sensors for easy system integration and better isolation between transmitter and receiver subsystems. First experimental tests on board a 3.2 m wingspan commercial radio-controlled aircraft are presented. The SAR images of a field close to an urban area have been focused using a back-projection algorithm. Using the dual channel capability, a single pass interferogram and Digital Elevation Model (DEM) has been obtained which agrees with the scene topography. A simple Motion Compensation (MoCo) module, based on the information from an Inertial+GPS unit, has been included to compensate platform motion errors with respect to the nominal straight trajectory. [ABSTRACT FROM AUTHOR]

This paper presents a novel technique for automatic edge enhancement and detection in synthetic aperture radar (SAR) images. The characteristics of SAR images justify the importance of an edge enhancement step prior to edge detection. Therefore, this paper presents a robust and unsupervised edge enhancement algorithm based on a combination of wavelet coefficients at different scales. The performance of the method is first tested on simulated images. Then, in order to complete the automatic detection chain, among the different options for the decision stage, the use of geodesic active contour is proposed. The second part of this paper suggests the extraction of the coastline in SAR images as a particular case of edge detection. Hence, after highlighting its practical interest, the technique that is theoretically presented in the first part of this paper is applied to real scenarios. Finally, the chances of its operational capability are assessed. [ABSTRACT FROM AUTHOR]

Radar data have already proven to be compressible with no significant losses for most of the applications in which it is used. In the framework of information theory, the compressibility of a signal implies that it can be decomposed onto a reduced set of basic elements. Since the same quantity of information is carried by the original signal and its decomposition, it can be deduced that a certain degree of redundancy exists in the explicit representation. According to the theory of compressive sensing (CS), due to this redundancy, it is possible to infer an accurate representation of an unknown compressible signal through a highly incomplete set of measurements. Based on this assumption, this paper proposes a novel method for the focusing of raw data in the framework of radar imaging. The technique presented is introduced as an alternative option to the traditional matched filtering, and it suggests that the new modes of acquisition of data are more efficient in orbital configurations. In this paper, this method is first tested on 1-D simulated signals, and results are discussed. An experiment with synthetic aperture radar (SAR) raw data is also described. Its purpose is to show the potential of CS applied to SAR systems. In particular, we show that an image can be reconstructed, without the loss of resolution, after dropping a large percentage of the received pulses, which would allow the implementation of wide-swath modes without reducing the azimuth resolution. [ABSTRACT FROM AUTHOR]

In this paper, bistatic interferometry using fixed-receiver configurations is addressed both theoretically and experimentally. The analytical expressions for interferometric phase and height sensitivity are derived, and a full interferometric processing chain for digital elevation model (DEM) generation is presented. The derived expressions are general, and they can be applied to two possible acquisition geometries: backscattering and forward scattering. The theoretical developments are complemented with experimental results done with the bistatic receiver Synthetic Aperture radar Bistatic Receiver for INterferometric Applications. The obtained DEMs are compared with a DEM from the Shuttle Radar Topography Mission and a digital terrain model from the Institut Cartografic de Catalunya. The comparison allows one to validate the results and demonstrate to which particular features of the scene that the bistatic radar is sensitive. [ABSTRACT FROM AUTHOR]

This paper uses a complete and realistic SAR simulation processing chain, GRECOSAR, to study the potentialities of Polarimetric SAR Interferometry (POLInSAR) in the development of new classification methods for ships. Its high processing efficiency and scenario flexibility have allowed to develop exhaustive scattering studies. The results have revealed, first, vessels' geometries can be described by specific combinations of Permanent Polarimetric Scatterers (PePS) and, second, each type of vessel could be characterized by a particular spatial and polarimetric distribution of PePS. Such properties have been recently exploited to propose a new Vessel Classification Algorithm (VCA) working with POLInSAR data, which, according to several simulation tests, may provide promising performance in real scenarios. Along the paper, explanation of the main steps summarizing the whole research activity carried out with ships and GRECOSAR are provided as well as examples of the main results and VCA validation tests. Special attention will be devoted to the new improvements achieved, which are related to simulations processing a new and highly realistic sea surface model. The paper will show that, for POLInSAR data with fine resolution, VCA can help to classify ships with notable robustness under diverse and adverse observation conditions. [ABSTRACT FROM AUTHOR]

The article discusses the advantages of the scattering-based model in responding to synthetic apertureradar (SAR) signature of complex targets. The author states that the 3D position and polarimetric scattering mechanism of the model allows to link the reflectivity information of SAR images with the macroscale structure of targets. Moreover, the proposed modeling approach minimize the amount of real images required for testing the model. Furthermore, the model has been confirmed to be an effective tool for ships and urban-like targets.

This paper presents a synthetic aperture radar (SAR) simulator that is able to generate polarimetric SAR (POLSAR) and polarimetric inverse SAR data of complex targets. It solves the electromagnetic problem via high-frequency approximations, such as physical optics and the physical theory of diffraction, with notable computational efficiency. In principle, any orbital monostatic sensor working at any band, resolution, and operating mode can be modeled. To make simulations more realistic, the target's bearing and speed are considered, and for the particular case of vessels, even the translational and rotational movements induced by the sea state. All these capabilities make the simulator a powerful tool for supplying large amounts of data with precise scenario information and for testing future sensor configurations. In this paper, the usefulness of the simulator on vessel classification studies is assessed. Several simulated polarimetric images are presented to analyze the potentialities of coherent target decompositions for classifying complex geometries, thus basing an operational algorithm. The limitations highlighted by the results suggest that other approaches, like POLSAR interferometry, should be explored. [ABSTRACT FROM AUTHOR]

Fractal geometry provides reliable models to describe geometrical properties of natural surfaces. Therefore, their use in the electromagnetic scattering methods deserves careful research. In order to have complete insight into the phenomenon, a measurement campaign on a fractal surface in a controlled environment is a key step. In this paper, we propose a technique for building a fractal surface that can be used for electromagnetic scattering evaluation purposes. The surface characteristics are imposed by computer synthesizing a bandlimited Weierstrass-Mandelbrot function, whose actual shape is constructed by means of a cheap innovative technique: the synthesized surface is made from cardboard covered with aluminum foil, which gives a conducting surface and creates the micro-scale conditions, useful to represent manufacturing errors. Statistics of the overall surface shape are then measured, analyzed and compared with the imposed ones, providing and verifying the rationale for a fully controlled surface to be applied in any kind of experiment on natural surfaces. [ABSTRACT FROM AUTHOR]

In this paper, an advanced technique for the generation of deformation maps using synthetic aperture radar (SAR) data is presented. The algorithm estimates the linear and nonlinear components of the displacement, the error of the digital elevation model (DEM) used to cancel the topographic terms, and the atmospheric artifacts from a reduced set of low spatial resolution interferograms. The pixel candidates are selected from those presenting a good coherence level in the whole set of interferograms and the resulting nonuniform mesh tessellated with the Delauney triangulation to establish connections among them. The linear component of movement and DEM error are estimated adjusting a linear model to the data only on the connections. Later on, this information, once unwrapped to retrieve the absolute values, is used to calculate the nonlinear component of movement and atmospheric artifacts with alternate filtering techniques in both temporal and spatial domain. The method presents high flexibility with respect be required number of images and the baselines length. However, better results are obtained with large diastases of short baseline interferograms. The technique has been tested with European Remote Sensing SAR data from an area of Catalonia (Spain) and validated with on-field precise leveling measurements. [ABSTRACT FROM AUTHOR]

This letter presents a technique to detect and correct phase errors appearing in interferometric airborne synthetic aperture radar (SAR) systems due to the lack of precision in the navigation system. The technique is based on a multisquint processing approach, i.e., by processing the same image pairs with different squint angles we can combine the information of different interferograms to obtain the desired phase correction. Airborne single-pass interferometric data from the Deutsches Zentrum für Luft- und Raumfahrt (DLR) Experimental airborne SAR is used to validate the method. [ABSTRACT FROM AUTHOR]

Reports on the application of the developed multiplicative regularized contrast source inversion method to microwave biomedical data. Description of the inversion method; Significance of the method for the solution of the inverse scattering problem; Advantage of the multiplicative regularizer.

Presents a study which investigated the systematic assessment of the major sources of experimental and model noise of Newton-Kantorovich reconstruction techniques for microwave tomography. Description of microwave scanner; Reconstruction methods; Illustration of the impact of temperature and frequency on the reconstruction of the dielectric contrast in a biological target.

Ground subsidences, either caused by natural phenomena or human activities, can threaten the safety of nearby infrastructures and residents. Among the different causes, mining operations can trigger strong subsidence phenomena with a fast nonlinear temporal behaviour. Therefore, a reliable and precise deformation monitoring is of great significance for safe mining and protection of facilities located above or near the mined-out area. Persistent Scatterer Interferometry (PSI) is a technique that uses stacks Synthetic Aperture Radar (SAR) images to remotely monitor the ground deformation of large areas with a high degree of precision at a reasonable cost. Unfortunately, PSI presents limitations when monitoring large gradient deformations when there is phase ambiguity among adjacent Persistent Scatterer (PS) points. In this paper, an improvement of PSI processing, named as External Model-based Deformation Decomposition PSI (EMDD-PSI), is proposed to address this limitation by taking advantage of an external model. The proposed method first uses interferograms generated from SAR Single Look Complex (SLC) images to optimize the parameter adjustments of the external model. Then, the modelled spatial distribution of subsidence is utilized to reduce the fringes of the interferograms generated from the SAR images and to ease the PSI processing. Finally, the ground deformation is retrieved by jointly adding the external model and PSI results. In this paper, fourteen Radarsat-2 SAR images over Fengfeng mining area (China) are used to demonstrate the capabilities of the proposed method. The results are evaluated by comparing them with leveling data of the area covering the same temporal period. Results have shown that, after the optimization, the model is able to mimic the real deformation and the fringes of the interferograms can be effectively reduced. As a consequence, the large gradient deformation then can be better retrieved with the preservation of the nonlinear subsidence term. The ground truth shows that, comparing with the classical PSI and PSI with unadjusted parameters, the proposed scheme reduces the error by 35.2% and 20.4%, respectively. [ABSTRACT FROM AUTHOR]

This work addresses the suitability of using X-band Synthetic Aperture Radar (SAR) data for operational geotechnical monitoring of site scale slow moving landslides, affecting urban areas and infrastructures. The scale of these studies requires high resolution data. We propose a procedure for the practical use of SAR data in geotechnical landslides campaigns, that includes an appropriate dataset selection taking into account the scenario characteristics, a visibility analysis, and considerations when comparing advanced differential SAR interferometry (A-DInSAR) results with other monitoring techniques. We have determined that Sentinel-2 satellite optical images are suited for performing high resolution land cover classifications, which results in the achievement of qualitative visibility maps. We also concluded that A-DInSAR is a very powerful and versatile tool for detailed scale landslide monitoring, although in combination with other instrumentation techniques. [ABSTRACT FROM AUTHOR]

Landslides are one of the most common and dangerous threats in the world that generate considerable damage and economic losses. An efficient landslide monitoring tool is the Differential Synthetic Aperture Radar Interferometry (DInSAR) or Persistent Scatter Interferometry (PSI). However, landslides are usually located in mountainous areas and the area of interest can be partially or even heavily vegetated. The inherent temporal decorrelation that dramatically reduces the number of Persistent Scatters (PSs) of the scene limits in practice the application of this technique. Thus, it is crucial to be able to detect as much PSs as possible that can be usually embedded in decorrelated areas. High resolution imagery combined with efficient pixel selection methods can make possible the application of DInSAR techniques in landslide monitoring. In this paper, different strategies to identify PS Candidates (PSCs) have been employed together with 32 super high-spatial resolution (SHR) TerraSAR-X (TSX) images, staring-spotlight mode, to monitor the Canillo landslide (Andorra). The results show that advanced PSI strategies (i.e., the temporal sub-look coherence (TSC) and temporal phase coherence (TPC) methods) are able to obtain much more valid PSs than the classical amplitude dispersion ( D A ) method. In addition, the TPC method presents the best performance among all three full-resolution strategies employed. The SHR TSX data allows for obtaining much higher densities of PSs compared with a lower-spatial resolution SAR data set (Sentinel-1A in this study). Thanks to the huge amount of valid PSs obtained by the TPC method with SHR TSX images, the complexity of the structure of the Canillo landslide has been highlighted and three different slide units have been identified. The results of this study indicate that the TPC approach together with SHR SAR images can be a powerful tool to characterize displacement rates and extension of complex landslides in challenging areas. [ABSTRACT FROM AUTHOR]

A preface to articles about the 2007 International Geoscience and Remote Sensing Symposium is presented.