Synthetic aperture radar tomography (TomoSAR) uses several coregistered images from different perspectives to reconstruct a power spectrum pattern (PSP) perpendicular to the line of sight (PLOS), enabling the estimation of a 3-D representation of the area. Classical estimators exhibit ambiguities and other undesired effects that are stronger for sparser and smaller stacks. To mitigate the limitations arising from a restricted number of acquisitions, we propose using a deep neural network (NN) to synthesize artificial tracks (i.e., images not contained in the original stack). The presented method utilizes a convolutional NN with an encoder-decoder architecture. We evaluate the proposed approach on real TomoSAR data from an airborne campaign over a forest region. The view estimation improves the tomographic results, offering robustness to scenarios affected by temporal decorrelation, which other classical methods, such as cubic convolution (CC), do not provide.

Most common focusing techniques for Synthetic Aperture Radar (SAR) Tomography (TomoSAR), e.g. Matched Spatial Filtering and Capon, make use of the conventional sample covariance matrix, obtained from a finite number of observations. Yet, structured covariance matrix estimates can be employed in lieu of the sample covariance matrix. Accordingly, our simulation study shows that Capon’s performance improves with the use of structured covariance matrices. These are obtained with the Subspace Fitting approach, properly adapted to TomoSAR. Numerical comparisons between structure and unstructured covariance matrices are presented.

Nonlinear inverse problems like Synthetic Aperture Radar Tomography are often ill-posed, since their solutions are very sensitive to small perturbations in the input data and are, therefore, difficult to compute numerically. Ill-posed problems are commonly tackled with regularization approaches; however, there is a crucial problem in regularization, related to the selection of regularization parameters. In the search for optimal values of such regularization parameters, this article addresses an extension of the L-curve method, called Θ-curve. Furthermore, aimed at reducing converge time, the k-criterion is added, based on the first and second derivatives of the L-curve.

This paper provides an overview of the state of the art and an outlook on future developments of spaceborne Synthetic Aperture Radar (SAR) systems with multi-baseline imaging capability, such as 3D differential SAR interferometry (3D-DinSAR), polarimetric SAR interferometry (Pol-InSAR), tomography (TomoSAR), and holography (HoloSAR). The goal is to fill the multidimensional data space with additional information from images with different spatial and/or temporal baselines.

Polarimetric focusing techniques for synthetic aperture radar (SAR) tomography (TomoSAR) pursue finding optimal polarization combinations to extract the associated scattering mechanisms and height of reflectors. Regularization approaches like weighted covariance fitting (WCF), implemented in an iterative manner, attain finer resolution than conventional focusing techniques (e.g., Capon). Such approaches normally entail the selection of a regularization parameter and a first estimate of the power spectrum pattern. Regularization parameter selection via L-Curve method requires providing the scattering vector; nonetheless, it may not be always available, especially when not working at full resolution. Manipulations previously done to the data covariance matrix (e.g., pre-summing) must be equivalent in the scattering vector, which may not be at all times feasible. Accordingly, this article suggests modifying the L-Curve method to work exclusively with data covariance matrices. The proposed novel strategy is applied to WCF, considering single and dual channels. Iterations are stopped based on the Akaike information criterion.

The correct functioning of parametric focusing techniques [e.g., MUltiple SIgnal Classification (MUSIC)] require a proper selection of the model order. For such aim, a methodology based on the Kullback-Leibler information criterion is commonly employed. These methods perform well due to its propensity to choose relatively large model orders, which tend to retrieve good-fitted responses when the data generating mechanism is more complex than the models used to fit. However, some solutions can be misleading, since only the most proper model order (i.e., the actual number of targets) guaranties best performance. As an alternative, this work suggests employing statistical regularization instead of model order selection (MOS) approaches. First, a model with large order is chosen to perform focusing via parametric methods; subsequently, statistical regularization is applied, seeking to attain good-fitted solutions. To demonstrate the capabilities of the addressed novel strategy, Synthetic Aperture Radar (SAR) Tomography (TomoSAR) is considered as application.

The GeoWAM project aims to achieve high-resolution and highly-accurate digital elevation models (DEM) to monitor the evolution of tidal flats over the German North Sea. To achieve this, the dual-frequency/dual-baseline (DFDB) DEM generation approach, recently developed by DLR, was further expanded to include L-band data. Based in the experience obtained in the 2019 GeoWAM campaign with X- and S-band only, the addition of L-band for the 2020 campaign helps to deal with the decorrelation found in repeat-pass data and potentially allows the creation of new merged products. For the computation of phase and coherence, a new local fringe frequency approach was included to improve the final generated DEMs.

Multi-platform campaigns open up new opportunities and allow a comparison and analysis of SAR signatures of the same area at different frequency bands and incident angles. In this paper, we make use of two different sensor systems: DLR's pulsed F-SAR operating at X-, C- and L-band, and FHR's frequency-modulated continuous-wave (FMCW) MIRANDA35 operating at Ka-band. Main goals of the campaign include the comparison of high-resolution polarimetric signatures at different frequency bands, change detection, synchronized acquisition of ground moving targets and air-moving target indication (AMTI) experiments. We present the planning and implementation of the campaign and first results of the data processing.

Synthetic aperture radar (SAR) tomography (TomoSAR) is a remote sensing technique that allows for the 3-D representation of the illuminated areas, recovering the vertical distribution of the backscattered power at each range-azimuth position. In this context, and with the aim of retrieving feature-enhanced tomograms, this paper addresses a new multi-stage iterative method that operates robustly in real-world TomoSAR operating scenarios with irregularly distributed acquisition constellations and only few available looks. The addressed approach alleviates the drawbacks of the conventional matched spatial filter (MSF) technique, which retrieves high ambiguity levels when irregular sampling is considered. Also, it alleviates the drawbacks of the commonly used Capon beamforming technique, which results to be inapplicable when the involved data covariance (structure) matrices are rank deficient. The addressed novel method combines the descriptive experiment design regularization (DEDR) framework for enhanced image reconstruction, with the wavelet domain thresholding (WDT)-based sparsity promoting refinement in the wavelet transform (WT) domain. The capabilities of the addressed WDT-refined virtual adaptive beamforming (VAB) approach, which we refer to as WAVAB, are corroborated via processing P-band airborne TomoSAR data of the German Aerospace Center (DLR), acquired by the E-SAR system over the test site located at the Vindeln municipality, northern Sweden, in 2008.

In May-June 2015 UAVSAR was flown to Europe to collect data in support of experiments in Iceland, Norway and Ger-many. The deployment in Germany was focused on PolIn-SAR and tomographic data collections at the Traunstein Forest and in the Munich urban area. In this paper we describe tomographic processing of the Munich data and comparison with in situ ground truth data.

Speckle is inherent to all coherent imaging systems and affects SAR imagery in the form of strong intensity variations in pixels with similar backscattering coefficient, difficulting the interpretation of SAR data. In the context of the Beltrami filter, a polarimetric distance is utilized as part of a region growing algorithm to find and then average similar covariance matrices within a central window using an iterative scheme. The Beltrami filter has shown good results using a computationally expensive geodesic distance that takes into account the Hermitian positive definite nature of the polarimetric covariance matrices. The flexible nature of the Beltrami distance allows for the use of any polarimetric distance, allowing the study on the utilization of less computationally complex distances and their impact on speckle reduction. In this paper, an analysis on the effect of some of the commonly utilized polarimetric synthetic aperture radar (PolSAR) distances measures within the Beltrami despeckling filter will be presented.

Synthetic aperture radar (SAR) tomography (TomoSAR) employs array signal processing techniques, in order to estimate the location of the vertical structures that compose the backscattering field, in the direction perpendicular to the line-of-sight (PLOS). Due to the limited number of tracks for practical TomoSAR sensing scenarios, it becomes challenging to accurately estimate the source parameters. Additionally, irregular sampling and non-uniform acquisition constellations introduce artifacts and increase ambiguity. The usage of super-resolved parametric methods and compressed sensing (CS) based approaches, improve the vertical resolution and mitigate the effect of sidelobes. However, parametric approaches have the main drawback related to the assumption that the scene is composed by a known finite number of point-type backscattering sources. Also, the CS-based techniques regularly imply a considerable computational burden. Overcoming the disadvantages of the above mentioned TomoSAR-adapted methods, this paper presents a novel non-parametric iterative approach for feature enhanced SAR tomography, in the context of maximum likelihood (ML) estimation theory. The feature enhancing capabilities of the proposed technique are corroborated via processing L-band airborne TomoSAR data of the German Aerospace Center (DLR), acquired by the F-SAR system over the forested test site of Froschham, Germany, in 2017.

This paper presents first the performance analysis of the state-of-the-art multi-channel SAR signal reconstruction algorithms that suffer from the geometrical approximations. Then, it proposes a two-step signal reconstruction method for spaceborne large along-track baseline multistatic SAR constellations operated with a pulse repetition frequency (PRF) under the Nyquist rate. The suggested algorithm first applies a bulk polychromatic reconstruction in wavenumber domain and then compensates the residual range variance in range-Doppler domain. This simple modification helps to reduce overall phase errors in the reconstruction process of the analysed case with respect to the state-of-the-art algorithms by about one order of magnitude. The performance of the algorithm is verified by showing the results in point target simulations for a multistatic X-band constellation with a resolution of about 15 times the carrier wavelength.

One of the main objectives of the upcoming space missions, such as Tandem-L and BIOMASS, is to map, on a global scale, the forest structure by means of synthetic aperture radar (SAR) tomography (TomoSAR). On one hand, the number of baselines is constrained to the revisit time that avoids temporal decorrelation issues. On the other hand, enhanced resolution is desired, since the forest structure is characterized from the vegetation layers that compose it, reflected in the tomographic profiles as local maxima. The TomoSAR nonlinear ill-conditioned inverse problem is conventionally tackled within the direction-of-arrival (DOA) estimation framework. The DOA-inspired nonparametric techniques are well suited to cope with distributed targets; nonetheless, the achievable resolution highly depends on the span of the tomographic aperture. Alternatively, superresolved parametric approaches have the main drawback related to the white noise model assumption that guaranties the separation of the signal and noise subspaces. Overcoming the disadvantages of the aforementioned techniques, in this letter, we address a novel maximum-likelihood (ML) inspired adaptive robust iterative approach (MARIA) for feature-enhanced TomoSAR reconstruction. MARIA performs resolution enhancement, with suppression of artifacts and ambiguity levels reduction, to an initial estimate of the continuous power spectrum pattern. After convergence, an accurate location of the closely spaced phase centers is achieved, easing the characterization of the forest structure. The feature-enhancing capabilities of the proposed approach are corroborated using airborne F-SAR data of the German Aerospace Center (DLR).

Large along-track baselines introduce residual polychromatic quadratic phase components which decrease the performance of state-of-the-art multichannel/multiplatform SAR reconstruction algorithms. This letter investigates the impact of the geometrical approximations in signal reconstruction methods for spaceborne multistatic SAR constellations with large along-track baselines operated with a pulse repetition frequency (PRF) under the Nyquist rate required for a single platform. We characterize and quantify the impact of these approximations, especially severe in the case of kilometric baselines and resolutions around 15λ. Finally, we put forward a generalized range-Doppler strategy to accommodate the geometry of distributed along-track constellations in an accurate manner.

In this paper, a dual-frequency and dual-baseline (DFDB) processing framework for the extraction of high-precision terrain information from airborne interferometric synthetic aperture radar (SAR) data is presented. Specifically, we propose the use of two single-pass data sets acquired simultaneously in two different frequency bands and two large-baseline repeat-pass data sets also acquired simultaneously in two frequency bands. The configuration profits from the stability of the single-pass derived elevation maps in relation to spatially correlated artifacts as well as from the increased sensitivity associated with large-baseline acquisitions. Moreover, the dual-frequency nature of the data set enables the tackling of the phase unwrapping issue, promoting the retrieval of unambiguous measurements. Several algorithms for the interferometric processing of the DFDB airborne data set are proposed, including the outline of multichannel phase calibration and unwrapping error correction strategies and approaches to remove spatially correlated artifacts and extract the common underlying topography. Elevation models generated from a DFDB data set acquired with the airborne F-SAR sensor over tidal flats in northern Germany are presented, and comparisons with an airborne laser scanner reference show errors with a standard deviation of around 14 cm and a mean absolute deviation of less than 10 cm.

Despite its ability to characterize 3-D environments, synthetic aperture radar (SAR) tomographic imaging, when applied to the characterization of targets concealed beneath forest canopies, may appear as an ill-conditioned estimation problem, with a complex mixture of numerous scattering mechanisms measured from a few different positions. Among the set of tomographic estimators that may be used to characterize such complex scattering environments, nonparametric tomographic techniques are more robust to focus on artifacts but limited in resolution and, hence, may fail to discriminate objects, whereas parametric ones provide better vertical resolution but cannot adequately handle continuously distributed volumetric scattering densities, characteristic of forest canopies. This letter addresses a new wavelet-based sparse tomographic estimation method for the 3-D imaging and discrimination of underfoliage objects that overcomes these limitations. The effectiveness of this new approach is demonstrated using L-band airborne tomographic SAR data acquired by the German Aerospace Center over Dornstetten, Germany.

With the relentless increase in population density, the anthropogenic expansion into natural terrestrial hazard zones has become irreversible resulting in ever more catastrophic disasters, not only in the Asia-Pacific region more so within the entire tropical belt engulfing Mother Earth. Thus not only the Indonesian Pacific Islands, so also South America, Africa and back via the Islands of the Indian Ocean to Asia-Pacific, these natural events like volcano eruptions, earthquakes with emerging tsunami, cyclones and severe down pours, humidity and haze have caused havoc, loss of lives, destruction of infrastructure and above all intentional manmade interference resulting in the deterioration of pristine tropical jungle forests. Matters have become so bad that proposals are forthcoming for equating oil-palm and tropical-fruit orchard mono-cultures with pristine tropical jungle habitat by greedy developers mostly exterior to local environmental regions suffering helplessly from it.

The ground-volume separation of radar scattering plays an important role in the analysis of forested scenes. For this purpose, the data covariance matrix of multi-polarimetric (MP) multi-baseline (MB) SAR surveys can be represented thru a sum of two Kronecker products composed of the data covariance matrices and polarimetric signatures that correspond to the ground and canopy scattering mechanisms (SMs), respectively. The sum of Kronecker products (SKP) decomposition allows the use of different tomographic SAR focusing methods on the ground and canopy structural components separately, nevertheless, the main drawback of this technique relates to the rank-deficiencies of the resultant data covariance matrices, which restrict the usage of the adaptive beamforming techniques, requiring more advanced beamforming methods, such as compressed sensing (CS). This paper proposes a modification of the nonparametric iterative adaptive approach for amplitude and phase estimation (IAA-APES), which applied to MP-MB SAR data, serves as an alternative to the SKP-based techniques for ground-volume reconstruction, which main advantage relates precisely to the non-need of the SKP decomposition technique as a pre-processing step.

The NASA/JPL UAVSAR system was deployed to Europe in the May-June 2015 to collect data in support of experiments in Iceland, Norway and Germany. The deployment in Germany was focused on PolInSAR and tomographic data collections at the Traunstein Forest and in the Munich urban area. In addition data were collected at Kaufbeuren, the DLR calibration site, where several surveyed corner reflectors were available for imaging. We describe the experiment design, data collections and present some preliminary results from these experiments.

SAR imaging of concealed targets beneath the canopies has to face a complex mixture of diverse scattering mechanisms. To characterize this complex scattering environment, nonparametric tomographic estimators are more robust to focusing artefacts but limited in resolution. Parametric tomographic estimators provide better vertical resolution but fail to adequately characterize continuously distributed volumetric scatterers such as forest canopies. To overcome these limitations, this paper addresses a new wavelet-based sparse estimation method for 3D imaging and characterization for underfoliage objects. The effectiveness of this new approach is demonstrated by using L-band Multi-Baseline PolInSAR Data over Dornstetten, Germany.

This paper provides an overview of the future development of spaceborne SAR systems with multi-baseline imaging capability like polarimetric SAR interferometry (PolInSAR), tomography (TomoSAR) and holography (HoloSAR). The goal is to fill the multi-dimensional data space with additional information from acquisitions having different spatial or temporal baselines. Multi-baseline imaging opens the door for a new class of image products in spaceborne SAR. Well-known examples are across-track and along-track interferometry, which allow the measurement of surface topography, ground deformation, ocean currents as well as glacier movements. While across-track and along-track interferometry are well established techniques and have been widely used by current spaceborne SAR systems, PolInSAR, TomoSAR and HoloSAR are emerging techniques which are shaping the future development of spaceborne SAR. New mission concepts for multi-static SAR configurations with distributed and sparse arrays will pave the way for this development.

Recently, the 3-D backscattering distribution of forests and ice bodies has been factor of study with the HoloSAR imaging mode, showing its capabilities to obtain 3-D imaging reconstructions of volumes over 360° at very high resolution. In this paper, the first assessment of agricultural crops in the holographic SAR tomography (HoloSAR) mode is presented. The goal of this research is to investigate the retrieval of the three-dimensional backscattering of crop fields as a function of the azimuthal aspect angle and the tomographic constellation. To that end, a HoloSAR campaign was conducted at X-/C-band by DLR's F-SAR sensor in Wallerfing, Germany. The experimental results of this study show 2-D and 3-D polarimetric images, where the co-polar phase is analyzed qualitatively giving some indications about the kind of scattering mechanisms.

This paper presents a study of the processing chain for ice and glacier structures in the holographic SAR tomography (HoloSAR) mode. The algorithm is mainly based on the fast factorized back-projection (FFBP) to solve a three-dimensional space using fully polarimetric data. The motivation of HoloSAR in the cryosphere is mainly driven by recent investigations that have shown the capabilities of this mode to obtain 3-D imaging reconstructions of volumes over 360 ° at very high resolution. In this regard, a HoloSAR campaign was conducted at L-/P-band by DLR's F-SAR sensor in K-Transect, Greenland. The first experimental results of this study show a polarimetric analysis of the resulting images of a single circular flight, where the arc- and circular patterns of the 2-D images in the (x, y) plane already indicate significant wave penetration. The second part presents 3-D images obtained by the combination of the circular and vertical synthetic apertures, which enable an estimation of the vertical profile of the glacier. This mode potentially allows for a more accurate estimation of the vertical profile of ice sheets and bedrock.

The paper presents a comparison of automatic temporal change detection techniques on the basis of SAR data acquired during the 2015 DALO-ARCTIC campaign in Greenland. The data, acquired by DLR's F-SAR sensor, includes fully polarimetric imagery at X-, C-, S- and L-band with temporal baselines ranging from very short (less than one hour) to long (more than three weeks). Results for both coherent (interferometric) and incoherent (polarimetric) change detection are presented, compared and discussed, taking into account the known environmental conditions during and between data acquisitions. They suggest that natural environmental changes in Arctic regions, such as snow fall or thaw, have a significant impact on the polarimetric/interferometric SAR signal that can, in some cases, dominate the change detection result, especially for long temporal baselines.

Synthetic Aperture Radar (SAR) Tomography (TomoSAR) provides access to the three-dimensional (3D) structure of illuminated media by jointly focusing multiple SAR acquisitions. TomoSAR imaging can be understood in simple terms by considering that multiple SAR flight lines, or orbits, allow forming a bi-dimensional synthetic aperture, resulting in the possibility to resolve the targets not only in the range-azimuth plane, but also in elevation. This simple principle brings along unprecedented possibilities, providing a way to investigate the illuminated media based on a direct observation of their vertical structure. The aim of this paper is to provide the readers with a brief tutorial on the use of TomoSAR imaging in the remote sensing of distributed media, by presenting basic imaging principles, applications, signal processing methods, and identifying challenges for future tomographic SAR systems.

The objective of the NASA Soil Moisture Active Passive (SMAP) mission is to provide global measurements of soil moisture and freeze/thaw states. SMAP integrates L-band radar and radiometer instruments as a single observation system combining the respective strengths of active and passive remote sensing for enhanced soil moisture mapping. Airborne instruments are a key part of the SMAP validation program. Here, we present an airborne campaign in the Rur catchment, Germany, in which the passive L-band system Polarimetric L-band Multi-beam Radiometer and the active L-band system F-SAR of DLR were flown simultaneously on six dates in 2013. The flights covered the full heterogeneity of the area under investigation, i.e., the main land cover types and all experimental monitoring sites. Here, we used the obtained data sets as a test bed for the analysis of three active-passive fusion techniques: 1) estimation of soil moisture by passive sensor data and subsequent disaggregation by active sensor backscatter data; 2) disaggregation of passive microwave brightness temperature by active microwave backscatter and subsequent inversion to soil moisture; and 3) fusion of two single-source soil moisture products from radar and radiometer. Results indicate that the regression parameters β are dependent on the radar vegetation index. The best performance was obtained by the fusion of radiometer brightness temperatures and radar backscatter, which was able to reach the same accuracy as single-source coarse-scale radiometer soil moisture retrieval but on a higher spatial resolution.

In the last few years, interest in multicircular synthetic aperture radar (SAR) acquisitions has arisen as a consequence of the potential achievement of full 3-D reconstructions at very high resolution over 360° azimuth angle variation. In particular, SAR systems at low frequencies are sensitive to volumetric backscattering of semi-transparent media, and they allow the imaging of internal structures, such as forests. To achieve a full 3-D reconstruction, a 2-D synthetic aperture is required, consisting of a circular (azimuthal) and a vertical component. This 3-D capability can be understood as the result of the combination of holographic and tomographic techniques. In this paper, both techniques will be presented to establish the concept of holographic SAR tomography (HoloSAR). As a further investigation, this paper also presents an analytical expression of the 3-D impulse response function (IRF) of targets in and off the center of the illuminated area. The IRF is characterized by its spatial resolution and sidelobe power, both being a function of the radar resolution capabilities and the geometric acquisition. The second part of this paper presents a polarimetric analysis of HoloSAR tomograms. In particular, the polarimetric signature of scatterers in forested areas is investigated for three different focusing approaches, namely coherent imaging, incoherent imaging, and the generalized likelihood ratio test (GLRT). The three algorithms use the fast-factorized back-projection (FFBP) for individual circular trajectories, and the latter two use in addition compressive sensing (CS) to retrieve the complex reflectivity in elevation. The IRF is validated using a polarimetric L-band HoloSAR survey, which consists of 19 circular passes conducted by the German Aerospace Center's airborne F-SAR sensor over a test site in Kaufbeuren, Germany. The same data set is used for the analysis of the backscattering of forests. Results show a significant horizontal resolution improvement for distributed targets with the coherent imaging approach, whereas a better sidelobe suppression in the direction perpendicular to the line of sight is achieved for the incoherent imaging and the GLRT.

The TanDEM-X mission aims the generation of an accurate global Digital Elevation Model (DEM). On the other hand, due to their flexibility regarding baseline configuration, frequency of acquisition, time and revisit time, airborne SAR interferometers remain viable for the generation of DEMs with very high vertical and horizontal accuracies at a local scale. In this paper, we present an experiment demonstrating the beneficial use of a TanDEM-X intermediate DEM to support the generation of an elevation model from airborne SAR with relative vertical accuracy in the order of centimeters.

This paper presents an assessment of the backscattering of glaciers in the holographic SAR tomography (HoloSAR) mode. The motivation of HoloSAR in the cryosphere is mainly driven by recent investigations in the biosphere that have shown the capabilities of this mode to reconstruct volumes with 3-D imaging reconstructions over 360 ° at very high resolution. To that end, an HoloSAR campaign was conducted at L-band by the DLR's F-SAR sensor over the Findel glacier, Monte Rosa, Switzerland. The first part of this study shows a polarimetric analysis of the resulting images of a single circular flight, where the arc- and circular patterns of the 2-D images in the (x, y) plane already indicate wave penetration. The second part presents 3-D images obtained by the combination of the circular and vertical synthetic apertures, which enable an estimation of the vertical profile of snow, ice sheets and bedrock.

SAR tomography is a remote sensing technique, extending SAR interferometry, that allows three-dimensional imaging of multiple height-distributed point-like scatterers or volumetric targets. It allows, for example, to solve layover urban scatterers or to analyze the vertical structure of vegetation layers or other targets with significant penetration of the sensor's radiation (dry soil, ice layers, etc.). The ability to monitor the 3-D inner structure of volumetric targets and to extract information about the nature and location of ongoing scattering processes promises a break-through in key environmental problems. Indeed, structural parameters of volume scatterers in the biosphere and cryosphere, such as vegetation height and moisture content, forest vertical structure and biomass, or snow / ice depth and layering are critical inputs for ecological process modeling and enable effective monitoring of ecosystem change. The 3-D tomographic principle has been also extended to higher dimension in the more recent differential tomography methodology, producing 4-D (3-D + time) images bridging the gap between differential interferometry and SAR tomography. Due to their unique capabilities and potential, tomographic SAR techniques have gained significant attention during the last years and become established methods for analysis of all kinds of three-dimensional back-scattering scenarios. In particular, for future space-borne SAR sensors operating in longer wavelength, like BIOMASS, SAOCOM-CS or Tandem-L, it is planned to employ 3-D tomographic imaging modes on an operational basis. This paper aims to review the different state-of-the-art signal processing methods for three-dimensional SAR imaging, which have been developed during the last decade, and for four-dimensional differential tomography. The requirements, advantages and disadvantages of different techniques are assessed and compared and open issues to be addressed in future developments are pointed out.

Speckle noise is an inherent problem in coherent imaging systems such as synthetic aperture radar. It creates strong intensity fluctuations and hampers the analysis of images and the estimation of local radiometric, polarimetric, or interferometric properties. Synthetic aperture radar (SAR) processing chains thus often include a multilooking (i.e., averaging) filter for speckle reduction, at the expense of a strong resolution loss. Preservation of point-like and fine structures and textures requires to adapt locally the estimation. Nonlocal (NL)-means successfully adapt smoothing by deriving data-driven weights from the similarity between small image patches. The generalization of nonlocal approaches offers a flexible framework for resolution-preserving speckle reduction. We describe a general method, i.e., NL-SAR, that builds extended nonlocal neighborhoods for denoising amplitude, polarimetric, and/or interferometric SAR images. These neighborhoods are defined on the basis of pixel similarity as evaluated by multichannel comparison of patches. Several nonlocal estimations are performed, and the best one is locally selected to form a single restored image with good preservation of radar structures and discontinuities. The proposed method is fully automatic and handles single and multilook images, with or without interferometric or polarimetric channels. Efficient speckle reduction with very good resolution preservation is demonstrated both on numerical experiments using simulated data, airborne, and spaceborne radar images. The source code of a parallel implementation of NL-SAR is released with this paper.

A number of synthetic aperture radar (SAR) systems might work in interrupted operation for different purposes. Examples are cooperative bistatic SAR systems with a synchronization link between the transmitter and receiver or multistatic systems operating in receive-only mode, among others. As a direct consequence, the acquired raw data contain missing echoes presented in a periodical or random pattern. Since the missing raw data introduce artifacts in the processed images, recovery methods have to be applied. Usually, spectral-estimation-based interpolators can be used to recover data. Although such algorithms show good performance for pointlike targets, their efficiency is decreased for distributed scatterers. In this paper, we propose, for a coherent pair of SAR images, the use of the common information in one image to reconstruct the other and vice versa. The conditions required for the proper use of the approach are discussed, and the method is verified using simulated data. One special case of study is the TanDEM-X mission, where the cooperative nature of the bistatic operation requires the periodic exchange of information between the satellites in order to gather information for calibration and synchronization, creating a periodic missing data pattern in the raw data. For this case of study, the reconstruction methods based on spectral estimation are analyzed, and the proposed reconstruction using cross-information is validated.

A direct consequence of the TOPS acquisition geometry and the steering in azimuth of the antenna is the time-varying Doppler centroid within bursts. If this fact is not properly accommodated during SAR image formation, undesired distortions in both azimuth and range dimensions of the focused SAR images may appear. Azimuth distortions are caused by the local mismatch of both squint and topography. Range distortions arise from the inaccurate accommodation of the intrapulse motion of the platform, usually known as the stop-and-go approximation. Conventional spaceborne SAR image formation schemes will be, in general, unable to provide accurate TOPS SAR images. These distortions are discussed and evaluated for exemplary low-Earth-orbit SAR scenarios. Compensation strategies are presented and validated with TerraSAR-X TOPS data. A discussion of the potential impact on the Sentinel-1 interferometric-wide-swath and extra-wide-swath modes (i.e, TOPS) is also given.

The paper proposes a novel approach to object classification and segmentation in multi-channel (e.g. polarimetric) SAR data. The classifier is intended for particularly difficult problems, where objects of interest exhibit a high degree of radiometric, polarimetric and geometric heterogeneity, both within individual object instances and across the object category as a whole. Classification is based on a non-parametric characterization of scene contents that avoids model assumptions liable to fail in this scenario. The classifier structure is based on a combination of techniques developed for related problems in computer vision: the cascade architecture helps breaking down the problem into manageable stages while random forests provide a powerful framework for learning and combining discriminative classification rules. In addition, scale space techniques explicitly introduce non-local, contextual and geometric information into the classification process. Preliminary results illustrate the potential of the proposed approach with respect to the task of building segmentation in dual-polarized TerraSAR-X data.

The objective of the NASA Soil Moisture Active & Passive (SMAP) mission is to provide global measurements of soil moisture and its freeze/thaw state. The SMAP measurement approach is to integrate L-band radar and radiometer as a single observation system combining the respective strengths of active and passive remote sensing for enhanced soil moisture mapping. Airborne instruments will be a key part of the SMAP validation program. Here, we present an airborne campaign in the Rur catchment, Germany, in which the passive L-band system Polarimetric L-band Multi-beam Radiometer (PLMR2) and the active L-band system DLR F-SAR were flown on six dates in 2013. The flights covered the full heterogeneity of the area under investigation, i.e. all types of land cover and experimental monitoring sites. The obtained data sets are used as a test-bed for the analysis of existing and development of new active-passive fusion techniques.

The use of repeat-pass-large-baseline SAR interferometry to generate highly accurate digital elevation models (DEMs) has not been as exploit as the use of single-pass interferometry. This is mainly due to issues associated with the small height of ambiguities (HoAs) necessary to deliver the required height accuracy, and with the temporal and geometrical decorrelation typical of repeat-pass systems. Although airborne systems are very attractive for the flexible baseline choice in repeat-pass mode, when using airborne datasets, the processing of the DEMs should account for uncompensated residual motion errors and other phase artefacts. In this paper we describe a methodology for generating accurate DEMs combining single- and repeat-pass data from dual frequency (X- and S-band) F-SAR acquisitions.

The spaceborne SAR geometry is space-variant due to the curved orbit and Earth's rotation. A first effect is the azimuth variance, which in current missions is accommodated by processing the data in azimuth blocks larger than the synthetic aperture and updating the processing parameters of the kernel. However, such option is not valid when the variation occurs within the observation time, as it happens in high-resolution modes. A second effect occurs due to the topography dependence of the geometry, i.e., targets at the same zero-Doppler slant-range distance but different altitudes have slightly different range curvatures. This topography dependence is neglected in current SAR missions. However, it has been recently shown that in very high-resolution spaceborne SAR image formation (e.g., resolutions a factor 10 of the wavelength or smaller) the azimuth- and topography-dependence become critical. This paper analyses first these two effects and then proposes a processing scheme to efficiently handle the geometry. The suggested approach is validated with simulations and TerraSAR-X staring spotlight data.

In this paper, we provide a systematic overview on bistatic SAR image formation for arbitrary platform trajectories. Bistatic SAR may offer improved flexibility, performance and cost-efficiency if compared to monostatic SAR systems certainly at the expense of increased operational complexity. In the previous years, the road from experimental to operational bistatic radar systems has been paved with the launch of TanDEM-X [1], the first bistatic SAR in space. Future bistatic SAR systems will encompass multistatic constellations and formations with large baselines capable of delivering novel Earth observation products with improved performance and coverage. In this context, efficiency and accuracy in bistatic SAR image formation becomes an important challenge, asking for the development of suitable signal processing algorithms. This paper describes first the relevant developments on bistatic SAR image formation. The validity and shortcomings of previously suggested approaches for different bistatic geometries is systematically discussed. An overview on bistatic SAR image formation is provided, stressing those key techniques and algorithms which, in our opinion, are applicable in future operational systems and missions; the theoretical background is complemented by results from multiple pioneering airborne, spaceborne, and hybrid air-/spaceborne bistatic SAR experiments conducted at DLR over the past decade.

Multicircular synthetic aperture radar (SAR) (MCSAR) is an extension of circular SAR (CSAR) characterized by the formation of a synthetic aperture in elevation with several circular flights. This imaging mode allows an improved resolution in the plane perpendicular to the line of sight ( LOS⊥), thus suppressing the 3-D cone-shaped sidelobes that are formed when focusing with CSAR. This letter presents the first polarimetric MCSAR airborne experiment acquired at P-band by the German Aerospace Center (DLR)'s F-SAR system over a forested area in Vordemwald, Switzerland. This letter also includes a phase calibration method based on the singular value decomposition (SVD) using ground signatures to estimate constant phase offsets within a stack of 2-D images. Focusing methods, such as fast-factorized back projection (FFBP), beamforming (BF), and compressive sensing (CS), described in previous publications are used to solve the complex reflectivity in the (x, y, z) space.

This contribution addresses the efficient evaluation of Fourier-based kernels for synthetic aperture radar (SAR) image formation. The goal is to evaluate the quality of the focused impulse response function and the residual phase errors of the kernel without having to implement the processor itself nor perform a costly point-target simulation followed by the processing. The proposed methodology is convenient for situations where the assumption of a hyperbolic range history does not hold anymore, and hence a compact analytic expression of the point target spectrum is not available. Examples where the hyperbolic range history does not apply include very high-resolution spaceborne SAR imaging or bistatic SAR imaging. The approach first computes numerically the two-dimensional (2D) spectrum of a point target and then uses the transfer function of the focusing kernel to match it, and hence obtain the impulse response function (IRF). The methodology is validated by comparing the matched IRFs with the ones obtained using point-target simulations.

This paper presents the first fully polarimetric high-resolution circular synthetic aperture radar (CSAR) images at L-band (1.3 GHz). The circular data were acquired in 2008 by the Experimental SAR (E-SAR) airborne system of the German Aerospace Center (DLR) over the airport of Kaufbeuren, Germany. The obtained images resulting from the coherent integration of the whole circular flight are investigated and discussed in terms of two of the main CSAR properties, namely, the theoretical subwavelength resolution in the horizontal plane (x, y) and the 3-D imaging capabilities. The 3-D imaging capabilities are of special interest due to the penetration of L-band in vegetated areas. These results were compared with images processed by the incoherent addition of the full synthetic aperture. The coherent approach showed a better performance since scatterers are focused at their maximum resolution. Due to the nonlinearity of the tracks and the high-computational burden, an efficient fast factorized back-projection (FFBP) has been developed. Unlike frequencydomain processors, it accommodates azimuthal variances and topography changes. Limits and considerations of the proposed algorithm are described and discussed. To further accelerate this process, the FFBP was also implemented in a graphics processing unit (GPU). Processing performance has been assessed with the direct BP (DBP) as a reference, obtaining speedup factors up to 1800. Residual motion errors have been estimated with a new frequency-based autofocus approach for CSAR configurations based on low signal-to-clutter ratio (SCR) isotropic scatterers. High-resolution images of man-made and distributed scatterers have been analyzed and compared with a stripmap SAR, both concerning anisotropic and isotropic-like scatterers. Results include a single-channel tomogram of a Luneburg lens and a fully polarimetric tomogram of a tree.

This paper addresses several important aspects that need to be considered for the processing of spaceborne synthetic aperture radar (SAR) data with resolutions in the decimeter range. In particular, it will be shown how the motion of the satellite during the transmission/reception of the chirp signal and the effect of the troposphere deteriorate the impulse response function if not properly considered. Further aspects that have been investigated include the curved orbit, the array pattern for electronically steered antennas, and several considerations within the processing itself. For each aspect, a solution is proposed, and the complete focusing methodology is expounded and validated using simulated point targets and staring spotlight data acquired by TerraSAR-X with 16-cm azimuth resolution and 300-MHz range bandwidth.

This paper addresses under-foliage target detection using diverse detection schemes. Compared with classical detection schemes as GLRT and SSF-based detection, isolated scatterer selection is potential to eliminate volume effects and detect under-foliage targets. The full-rank polarimetric spectral estimators are also applied for under-foliage detection. The effectiveness of diverse detection schemes are demonstrated by using L-band Multi-Baseline PolInSAR Data over Dornstetten, Germany.

Missing echoes in the raw data introduce artifacts that might be noticeable in processed SAR images. As a consequence, recovery methods must be applied to ensure the high quality of the images. Although spectral estimation based interpolators are suitable for the recovery of point-like targets, their efficiency is poor for distributed ones. In this paper we propose a new reconstruction method for interferometric systems, which uses the common information in one image of a coherent pair to recover the other and vice versa. Since a typical example of missing data happens when acquiring with the bistatic mode of TanDEM-X, the proposed method is verified with data from a bistatic TanDEM-X survey in addition to simulated data. The results show that the proposed reconstruction can significantly improve the accuracy of the resulting interferograms.

This paper presents the first 3-D polarimetric holographic tomograms at L-band using fully polarimetric multi-circular SAR (MCSAR) over forested areas. This concept offers an innovative way of analyzing the Earth, in particular volume scatterers such as forested areas, ice and dry soils. Holographic tomograms are formed by low-frequency radar in L-band and by the acquisition of multi-angular measurements with MCSAR over 360°. MCSAR consists of the combination of CSAR with an additional synthetic aperture in height (z). The analysis of the impulse response function (IRF) of MCSAR shows 3-D sidelobe reduction and an improvement in the resolution along the z direction. A fully polarimetric MCSAR campaign using the DLR's F-SAR airborne system at L-band over the region of Kaufbeuren, Germany was carried out. Images in 3-D were focused with beamforming (BF) and compressive sensing (CS). Results depict advantages of MCSAR such as shadow reduction, low temporal decorrelation and a better understanding of the coherent 3-D radar backscattering.

This paper presents an analytical analysis of the impulse response function (IRF) of multi-circular SAR (MCSAR) as a function of the system bandwidth and the number of tracks, thereby optimizing the acquisition geometry to get the best 3-D resolution and sidelobe suppression. Moreover, the wide range of spectrum measurements provided by MCSAR allows the information retrieval over 360 °, thus understanding the anisotropic signature of scatterers, e.g. by their polarimetric signature. The second part of this paper presents a polarimetric analysis of the resulting holographic SAR tomograms of forested areas by means of the generalized likelihood ratio test (GLRT) algorithm, as well as by coherent and incoherent imaging. The IRF and the anisotropic analysis are validated with a polarimetric MCSAR campaign conducted at L-band by the DLR's F-SAR sensor over a forested region in Kauf-beuren, Germany.

The F-SAR airborne SAR instrument represents the successor of the E-SAR system of the German Aerospace Center (DLR), which has been extensively used in the last three decades. Its development was triggered by the current demand for data being simultaneously acquired at different wavelengths and polarisations, as well as by the demand for very high resolution in the order of decimetres. F-SAR is a modular development utilising the most modern hardware and commercial off the shelf components. F-SAR is designed to operate fully polarimetrically at X-, C-, S-, L- and P-bands and provides single- pass polarimetric interferometric capabilities in X- and S-bands. Additionally, up to four bands can be acquired simultaneously, partly even in polarimetric acquisition modes. This paper aims to present and evaluate the advanced multi-frequency polarimetric capabilities of the F- SAR system, as well as first results of single-pass polarimetric interferometry at X- and S-band.

This paper proposes a method for extracting the tropospheric time delay in a single-pass using SAR images acquired in squinted geometries. The required accuracies and error sources are analysed and a satellite configuration providing single-pass measurements of the tropospheric delay is proposed. Moreover, a joint topography-tropospheric delay estimation using very-high resolution SAR images is also suggested for cases where an inaccurate DEM is available. A performance of the approach with current TerraSAR-X staring spotlight like parameters is also computed.

The possibility of combining data acquired with different platforms to generate a single SAR image results in an advantageous relaxation of the timing and sampling requirements of the system which can be used to improve in different ways its performance. We report about a generalised approach for distributed SAR image formation which is based on a platform dedicated compensation of the observation geometry followed by a differential calibration of the data. The validity of the approach on simulated data is presented. Further tests with actual data from a TanDEM-X dedicated campaign are being conducted.

The distortions caused in conventionally focused TOPS SAR images which originate from the azimuth-variant Doppler centroid within a burst are presented and analyzed. In particular, the azimuth distortions due to topography mismatch in focusing stages and the range distortions due to the assumption of validity for the stop-and-go approximation are expounded in detail. Compensation strategies to accommodate the two effects in an accurate and precise manner are discussed and validated with TOPS data acquired with TerraSAR-X.

Super-resolution imaging via compressed sensing (CS)-based spectral estimators has been recently introduced to synthetic aperture radar (SAR) tomography. In the case of partial scatterers, the mainstream has so far been twofold, in that the tomographic reconstruction is conducted by either directly working with multiple looks and/or polarimetric channels or by exploiting the corresponding single-channel second-order statistics. In this letter, we unify these two methodologies in the context of covariance fitting. In essence, we exploit the fact that both vertical structures and the unknown polarimetric signatures can be approximated in a low-dimensional subspace. For this purpose, we make use of a wavelet basis in order to sparsely represent vertical structures. Additionally, we synthesize a data-adaptive orthonormal basis that spans the space of polarimetric signatures. Finally, we validate this approach by using fully polarimetric L-band data acquired by the E-SAR sensor of the German Aerospace Center (DLR).

During the last decade, synthetic aperture radar (SAR) became an indispensable source of information in Earth observation. This has been possible mainly due to the current trend toward higher spatial resolution and novel imaging modes. A major driver for this development has been and still is the airborne SAR technology, which is usually ahead of the capabilities of spaceborne sensors by several years. Today's airborne sensors are capable of delivering high-quality SAR data with decimeter resolution and allow the development of novel approaches in data analysis and information extraction from SAR. In this paper, a review about the abilities and needs of today's very high-resolution airborne SAR sensors is given, based on and summarizing the longtime experience of the German Aerospace Center (DLR) with airborne SAR technology and its applications. A description of the specific requirements of high-resolution airborne data processing is presented, followed by an extensive overview of emerging applications of high-resolution SAR. In many cases, information extraction from high-resolution airborne SAR imagery has achieved a mature level, turning SAR technology more and more into an operational tool. Such abilities, which are today mostly limited to airborne SAR, might become typical in the next generation of spaceborne SAR missions.

Synthetic aperture radar (SAR) tomography is a 3-D imaging modality that is commonly tackled by spectral estimation techniques. Thus, the backscattered power along the cross-range direction can be readily obtained by computing the Fourier spectrum of a stack of multibaseline measurements. In addition, recent work has addressed the tomographic inversion under the framework of compressed sensing, thereby recovering sparse cross-range profiles from a reduced set of measurements. This paper differs from previous publications, in that it focuses on sparse expansions in the wavelet domain while working with the second-order statistics of the corresponding multibaseline measurements. In this regard, we elaborate on the conditions under which this perspective is applicable to forested areas and discuss the possibility of optimizing the acquisition geometry. Finally, we compare this approach with traditional nonparametric ones and validate it by using fully polarimetric L-band data acquired by the Experimental SAR (E-SAR) sensor of the German Aerospace Center (DLR).

Super-resolution imaging via compressed sensing (CS) based spectral estimators has been recently introduced to synthetic aperture radar (SAR) tomography. In the case of partial scatterers, the mainstream has so far been twofold, in that the tomographic reconstruction is conducted by either working directly with multiple looks and/or polarimetric channels or by exploiting the corresponding single-channel second order statistics. In this paper, we unify these two methodologies in the context of covariance fitting. In essence, we exploit the fact that both vertical structures as well as the unknown polarimetric signatures can be approximated in a low dimensional subspace. For this purpose, we make use of a wavelet basis in order to sparsely represent vertical structures. Additionally, we synthesize a data adaptive orthonormal basis that spans the space of polarimetric signatures. Finally, we validate this approach by using fully polarimetric L-band data acquired by the E-SAR sensor of the German Aerospace Center (DLR).

The contribution of Polarimetric Synthetic Aperture Radar (PolSAR) images compared with the single-channel SAR in terms of temporal scene characterization has been found and described to add valuable information in the literature. Recently, a new PolSAR tracking algorithm has been proposed for glacier surface velocity monitoring. The proposed polarimetric tracking method applies Mutual Information (MI) to measure the statistical dependence between temporal polarimetric images, which is assumed to be maximum if the images are geometrically aligned. In this paper, its implementation of interest will be investigated.

This paper presents new principles and techniques to perform High Resolution (HR) 3-D imaging of volumetric environments using Polarimetric SAR Tomography (POLTOMSAR) and Multi-Baseline Polarimetric and Interferometric SAR (MB-POL-inSAR) data. Unlike classical polarimetric spectral estimation approaches which consider polarization as way to improve the discrimination between vertically aligned scatterers, this paper provides full rank techniques which permit to estimate 3-D coherency matrices that can be characterized using classical polarimetric processing algorithms.

The objective of the NASA Soil Moisture Active & Passive (SMAP) mission is to provide global measurements of soil moisture by fused active and passive L-band microwave measurements. With an airborne campaign conducted in the Rur catchment, Germany, in 2012, an active and passive L-band microwave data set is generated. The passive Polarimetric L-band Multi-beam Radiometer (PLMR2) and the active L-band system DLR F-SAR were installed on the DLR Dornier DO 228 aircraft. Despite of the differences between the airborne and the future spaceborne sensors, the data set will serve as a test bed for the analysis of existing and development of enhanced future active/passive data fusion techniques. Moreover, the derivation of (vegetation) parameters for the fusion approaches is planned.

The cooperative nature of the TanDEM-X mission bistatic operation allows the periodically exchange of information between transmitter and receiver over the SAR acquisition. With the information gathered during the synchronization (sync) events it is possible to perform the phase and time referencing necessary for the calibration of the bistatic SAR image. However, given that transmitter and receiver are dedicated to the link during the sync events, the reception of SAR signal is periodically interrupted leading to gaps in the SAR raw data. Consequently, the processed SAR image will be corrupted, especially when acquiring close to the Nyquist rate. The paper addresses different approaches based on parametric and non-parametric spectral estimation to reconstruct the missing data and presents results with SAR data from TerraSAR-X and TanDEM-X.

Three-dimensional reconstruction and sub-wavelength resolution can be achieved in Circular SAR (CSAR) mode with a single pass. However, circles or arcs are present when the assumed height during focussing is not that of the target. In 3-D imaging these artifacts are seen as cone-shaped sidelobes due to the poor resolution in the direction perpendicular to the line of sight. In this work, a multicircular fully polarimetric SAR experiment using DLR's F-SAR system at P-band is presented. The purpose is to enhance the resolution while focusing 3-D images by retrieving the backscattering profile in elevation. A phase calibration method using the Singular Value Decomposition (SVD) is presented. Processing methods such as Fast Factorized Back Projection for circular tracks, and reconstruction techniques with coherent averaging with beamforming and compressive sensing for 3-D are used. Finally, the first holographic SAR tomogram at P-Band of a forested area is presented.

This paper addresses several innovative steps needed in the chirp scaling and extended chirp scaling (ECS) algorithms in order to process staring Spotlight TerraSAR-X (TSX) images with 21 cm azimuth resolution and 300 MHz range bandwidth. The aspects that need of special consideration are the 2D phase truncation in frequency domain of ECS, the element pattern of the antenna array, the curved orbit, the stop-and-go approximation, and the troposphere. All these aspects are expounded in detail and a solution is given for each of them. The suggested corrections are applied at raw data level, hence easing the integration within the existing TSX processor. Real data acquired by TSX in the experimental staring Spotlight mode are used to validate the proposed methodology.

The F-SAR airborne SAR instrument represents the successor of the E-SAR system of the German Aerospace Center (DLR), which had previously been extensively used over the last three decades. Its development was triggered by the current demand for simultaneous acquisitions at different wavelengths and polarisations as well as by the demand for very high resolution in the order of decimetres. F-SAR is a modular development utilising state of the art hardware. As for E-SAR, DLRs Dornier DO228-212 aircraft is the first choice as platform for the new system. With the recently completed X-band single-pass interferometer and the P-band subsystem, F-SAR is now ready for fully replacing the E-SAR. This paper presents the two new subsystems and analyses their performance based on fully polarimetric imagery acquired during recent system test and calibration campaigns.

Launched in June 2010, TanDEM-X is an interferometric mission with the main goal of providing a high-resolution, global and unprecedentedly accurate digital elevation model (DEM) of the Earth by means of single-pass X-band SAR interferometry. Despite its usual quasi-monostatic configuration, TanDEM-X is the first genuinely bistatic SAR system in space. During its monostatic commissioning phase, the system was operated in pursuit monostatic mode. During that time, some pioneering bistatic SAR experiments with both satellites commanded in non-nominal modes were conducted with the main purpose of testing the performance of both space and ground segments in very demanding scenarios. In particular, this article includes results of the first bistatic acquisition and the first single-pass interferometric (mono/bistatic) acquisition with TanDEM-X, addressing their innovative aspects and focussing on the analysis of the experimental results. Even in the absence of essential synchronisation and calibration information, bistatic images and interferogramswith similar quality to pursuit monostatic have been obtained. Some months later, with TanDEM-X already in its operational DEM-acquisition phase a further challenging bistatic acquisition carried out in cooperation with DLR's airborne radar F-SAR has been carried out. The objective was to acquire fully polarimetric interferometric data with a high range of available bistatic angles. A dedicated commanding of both TanDEM-X and F-SAR was required, including irregular sampling schemes, partially missing bistatic echo reception and bistatic synchronisation, which pose a number of technological challenges in SAR data processing before the calibrated bistatic SAR images are obtained. This article reports about these two set of experiments.

In recent years, 3-D imaging by means of polarimetric synthetic aperture radar (SAR) sensors has become a field of intensive research. In SAR tomography, the vertical reflectivity function for every azimuth-range pixel is usually recovered by processing data collected using a defined repeat-pass acquisition geometry. The most common approach is to generate a synthetic aperture in the elevation direction through imaging from a large number of parallel tracks. This imaging technique is appealing, since it is very simple. However, it has the drawback that large temporal baselines can severely affect the reconstruction. In an attempt to reduce the number of parallel tracks, we propose a new approach that exploits structural correlations between neighboring azimuth-range pixels and/or polarimetric channels. As a matter of fact, this can be done under the framework of distributed compressed sensing (CS) (DCS), which stems from CS theory, thus also exploiting sparsity in the tomographic signal. Finally, results demonstrating the potential of the DCS methodology will be validated by using fully polarimetric L-band data acquired by the E-SAR sensor of the German Aerospace Center (DLR).

TanDEM-X (TerraSAR-X Add-on for Digital Elevation Measurements) is a high-resolution interferometric mission with the main goal of providing a global and unprecedentedly accurate digital elevation model of the Earth surface by means of single-pass X-band synthetic aperture radar (SAR) interferometry. Despite its usual quasi-monostatic configuration, TanDEM-X is the first genuinely bistatic SAR system in space. During its monostatic commissioning phase, the system has been mainly operated in pursuit monostatic mode. However, some pioneering bistatic SAR experiments with both satellites commanded in nonnominal modes have been conducted with the main purpose of validating the performance of both space and ground segments in very demanding scenarios. In particular, this letter reports about the first bistatic acquisition and the first single-pass interferometric (mono-/bistatic) acquisition with TanDEM-X, addressing their innovative aspects and focusing on the analysis of the experimental results. Even in the absence of essential synchronization and calibration information, bistatic images and interferograms with similar quality to pursuit monostatic have been obtained.

This paper proposes a new method for a measure of coherent similarity between temporal multichannel synthetic aperture radar (SAR) images and its implementation to change detection application. The method is based on mutual information (MI) from information theory. The MI measures the amount of information in common between coherent temporal multichannel SAR acquisitions. In order to develop an algorithm for all kinds of SAR images, such as interferometric SAR, polarimetric-interferometric SAR (PolInSAR), and partial PolInSAR, first, the joint density function of temporal multichannel images based on their second-order statistics has been derived. Then, the derived joint density function is used to calculate an analytical expression for the MI between temporal images, which is assumed to be maximal if the temporal images are identical. Although, in this paper, a new coherent similarity measure has analytically been derived for temporal polarimetric SAR images based on complex Wishart process in time, since the mathematical formulation is general, it can equally well be implemented into any kind of multivariate remote sensing data, such as multispectral optical and interferometric images after small continuation. This derived quantity has been implemented for change detection application whose aim is to characterize the temporal behavior of the acquisitions. A comparison between the proposed and the other well-known change detection methods by means of scene characterization is shown, describing the advantages due to the fact that the proposed change detector involves almost every facet of applied change detection.

This paper addresses the imaging of objects located under a forest cover using polarimetric synthetic aperture radar tomography (POLTOMSAR) at L-band. High-resolution spectral estimators, able to accurately discriminate multiple scattering centers in the vertical direction, are used to separate the response of objects and vehicles embedded in a volumetric background. A new polarimetric spectral analysis technique is introduced and is shown to improve the estimation accuracy of the vertical position of both artificial scatterers and natural environments. This approach provides optimal polarimetric features that may be used to further characterize the objects under analysis. The effectiveness of this novel technique for POLTOMSAR is demonstrated using fully polarimetric L-band airborne data sets acquired by the German Aerospace Center (DLR)'s E-SAR system over the test site in Dornstetten, Germany.

This paper presents results on SAR interferometry for data acquired in the Terrain Observation by Progressive Scans (TOPS) imaging mode. The rationale to retrieve accurate interferometric products in this mode is expounded, emphasizing the critical step of coregistration. Due to the particularities of the TOPS mode, a high Doppler centroid is present at burst edges, demanding a very high azimuth coregistration performance. A coregistration accuracy of around one tenth of a pixel, as it is usually recommended for stripmap interferometric data, could result in large undesired azimuth phase ramps in each TOPS burst. This paper presents two approaches based on the spectral diversity technique to precisely estimate this coregistration offset with the required accuracy and evaluates their performance. The effect of squint at burst edges in terms of an undesired impulse response shift during focusing and the impact on the interferometric coregistration performance is also addressed. Repeat-pass TOPS data acquired experimentally by TerraSAR-X are used to validate the proposed approaches.

In recent years, three-dimensional imaging by means of SAR tomography has become a field of intensive research. In SAR tomography, the vertical reflectivity function for every azimuth-range pixel is usually recovered by processing data collected using a defined repeat pass acquisition geometry. The most common approach is to generate a synthetic aperture in the elevation direction through imaging from a large number of parallel tracks. This imaging technique is appealing, since it is very simple. However, it has the draw back that large temporal baselines, which is the case for space-borne platforms, can severely affect the reconstruction. In an attempt to reduce the number of parallel tracks, we propose a new tomographic focusing approach that trades number of SAR images for correlations between neighboring azimuth-range pixels and polarimetric channels. As a matter of fact, this can be done under the framework of Distributed Compressed Sensing (DCS), which stems from Compressed Sensing (CS) theory, thus also exploiting sparsity in our tomographic signal. In addition, we address the problem of measurements affected by additive as well as multiplicative speckle noise. Results demonstrating the potential of the DCS methodology will be validated by using fully polarimetric L-band data acquired by the E-SAR sensor of DLR.

This paper presents principles and techniques to perform tomographic imaging of volumetric natural environments using Multi-Baseline Polarimetric and Interferometric SAR (MB POL-inSAR) data. The objective of this work is to provide robust techniques to reconstruct the 3-D structure of media and to estimate some of their physical parameters. The pro posed approaches are based on results obtained in [1] on the robust estimation of MB-POL-inSAR quantities, on the POLINSAR model presented in [2] and on the tomographic techniques introduced in [3] and [4].

This paper describes the implementation of an efficient implementation of a Fast Factorized Back Projection (FFBP) algorithm for Circular SAR (CSAR) trajectories for real air- borne data. Unlike Fourier-domain based focusing processors, this approach considers the azimuth variance and topography changes with high accuracy, while improving significantly the computational time factor in comparison with the direct Back Projection (BP). To further accelerate the focusing, the circular FFBP was implemented also on a Graphics Processor Unit (GPU). In the second part of the document is shown a fully polarimetric image of the region of Kaufbeuren, Germany, (acquired by the DLR's E-SAR system) focused with this method to the theoretical limit of ~λ/4 j. Thus, the efficiency, accuracy and performance of the circular FFBP is demonstrated, as well as the potential of CSAR when focusing over 360 °.

This paper reports on several experiments performed with the TerraSAR-X (TSX) and the TanDEM-X (TDX) satellites. The experiments consist in the generation of improved image products by coherently combining the images acquired individually by both satellites, hence the name distributed imaging. In the literature it has already been suggested the use of two or more satellites in close formation not only to have interferometric capabilities, but also to improve the azimuthal or range resolutions by performing the acquisitions simultaneously (no temporal decorrelation). This idea can be carried out by acquiring different portions of the spectrum and adding them coherently afterwards. Another possibility is to synthesize quad-pol acquisitions using dual-pol ones, an idea already carried out with airborne systems. Such experiments have been performed with TSX and TDX and are described in this paper.

The F-SAR airborne SAR instrument represents the successor of the E-SAR system of the German Aerospace Center (DLR), which has been extensively used in the last three decades. Its development was triggered by the current demand for data being simultaneously acquired at different wavelengths and polarisations as well as by the demand for very high resolution in the order of decimetres. F-SAR is a modular development utilising the most modern hardware and commercial off the shelf components. As for E-SAR DLRs Dornier DO228-212 aircraft is the first choice as platform for the new system. Although the F-SAR system is still under development, it is already taking over some of the operational duties of the old E-SAR system. This paper will analyse the performance of the current system, based on the multi-frequency and fully polarimetric imagery acquired during several campaigns in the last two years. Since F-SAR is using a fixed antenna mount without gimbal, precise radiometric calibration is particularly challenging, especially in the shorter wavelengths. Therefore, special emphasis is placed on the system calibration and the associated quality control including the achieved spatial resolution and radiometric accuracy in the different bands.

TanDEM-X is a high-resolution interferometric mission with the main goal of providing a global and unprecedentedly accurate digital elevation model (DEM) of the Earth surface by means of single-pass X-band SAR interferometry. De spite its usual quasi-monostatic configuration, TanDEM-X is the first genuinely bistatic SAR system in space. During its monostatic commissioning phase, the system has been mainly operated in pursuit monostatic mode. However, some pioneering bistatic SAR experiments with both satellites commanded in non-nominal modes have been conducted with the main purpose of testing the performance of both space and ground segments in very demanding scenarios. In particular, this paper reports about the first bistatic acquisition and the first single-pass interferometric (mono/bistatic) acquisition with TanDEM-X. Even in the absence of essential synchronisation and calibration information, bistatic images and interferograms with similar quality to pursuit monostatic have been obtained.

This paper introduces new polarimetric algorithms for generating 3-D images and estimating scattering mechanisms from polarimetric multibaseline (MB) interferometric synthetic aperture radar (SAR) measurements. First, an MB interferometric SAR signal model is generalized to the fully polarimetric configuration, establishing the notion of polarimetric reflectivity. Subsequently, polarimetric beamforming, Capon, and MUSIC methods that determine optimal polarization combinations for height estimation are developed. These new techniques allow for extracting the height of reflectors, the associated scattering mechanisms, and the polarimetric (pseudo)reflectivities. By means of polarimetric dual-baseline interferometric SAR observations of an urban environment, the performance of the conceived algorithms is examined in detail. Producing 3-D images of a building layover, the quality of the approaches is compared in terms of refined resolution and lowered side lobes. Furthermore, the scattering processes occurring in urban scenes are investigated thoroughly by analyzing the optimal reflection types. The algorithms are validated using dual-baseline polarimetric SAR interferometric data at L-band acquired by German Aerospace Center's experimental SAR system over Dresden city.

This paper proposes a new method for change detection measurement including whole SAR imaging modes such as PolIn- SAR, partial PolInSAR and InSAR in a set of multi-temporal multidimensional SAR images. The method is based on the special case of Kullback-Leibler (KL-divergence) test, known as Mutual Information. In order to develop an algorithm, firstly the joint distribution of PolInSAR data set, based on the second order statistics has been derived. Such a derivation accounts for the whole multi-temporal SAR images. Then the mutual information is used to measure the difference between the joint density of multi-temporal PolSAR data sets and their marginal density known as complex Wishart distribution. A comparison between the proposed and the other well-known change detection (e.g. cross correlation) technique is shown by means of real data, describing the advantages due to the fact that the proposed change detector involves almost every facet of the applied change detection.

SAR tomography is the extension of conventional two dimensional SAR imaging principle to three dimensions. In order to improve the vertical resolution with respect to classical Fourier-based methods, high resolution approaches are used in this paper to perform SAR tomography. Both nonparametric spectral estimators, like beamforming and Capon and parametric ones, like MUSIC, maximum likelihood, are applied to real data sets and compared in terms of scatterer location accuracy and resolution. This paper addresses the discrimination of coherent scatterers presented in the natural environment and a joint approach of estimation and detection is proposed.

TanDEM-X is a high-resolution interferometric radar mission with the main goal of providing a global digital elevation model (DEM) of the Earth surface by means of single-pass X-band SAR interferometry. It is, moreover, the first genuinely bistatic spaceborne SAR mission, and, independently of its usual quasi-monostatic configuration, includes many of the peculiarities of bistatic SAR. An experimental, versatile, and flexible interferometric chain has been developed at DLR Microwaves and Radar Institute for the scientific exploitation of TanDEM-X data acquired in non-standard configurations. The paper describes the structure of the processing chain and focusses on some essential aspects of its bistatic part. Some experimental results performed with TerraSAR-X demonstrate the flexibility of the implemented processor.

This paper concerns forest parameter retrieval from polarimetric interferometric synthetic aperture radar (PolInSAR) data considering two layers, one for the ground under the vegetation and one for the volumetric canopy. A model is designed to combine a physical model-based polarimetric decomposition with the random-volume-over-ground (RVoG) PolInSAR parameter inversion approach. The combination of a polarimetric scattering media model with a PolInSAR RVoG vertical structure model provides the possibility to separate the ground and the volume coherency matrices based on polarimetric signatures and interferometric coherence diversity. The proposed polarimetric decomposition characterizes volumetric media by the degree of polarization orientation randomness and by the particle scattering anisotropy. Using the full model enhances the estimation of the vertical forest structure parameters by enabling us to estimate the ground-to-volume ratio, the temporal decorrelation, and the differential extinction. For forest vegetation observed at L-band, this model accounts for the ground topography, forest and canopy layer heights, wave attenuation in the canopy, tree morphology in the form of the angular distribution and the effective shapes of the branches, and the contributions from the ground level consisting of surface scattering and double-bounce ground-trunk interactions, as well as volumetric understory scattering. The parameter estimation performance is evaluated on real airborne L-band SAR data of the Traunstein test site, acquired by the German Aerospace Center (DLR)'s E-SAR sensor in 2003, in both single- and multibaseline configurations. The retrieved forest height is compared with the ground-truth measurements, revealing, for the given test site, an average root-mean-square error (rmse) of about 5 m in the repeat-pass configuration. This implies an improvement in rmse by over 2 m in comparison to the pure coherence-based RVoG PolInSAR parameter inversion.

In this paper, the accuracy assessment of the recently proposed Maximum Likelihood (ML) texture tracking algorithm is discussed. Its comparison with the well known texture tracking technique, i.e., Normalized Incoherent Cross Correlation (NICC), has also been investigated in the case of the presence of multiplicative noise structure.

The Microwaves and Radar Institute of the German Aerospace Center (DLR) is known for consistent work on the field of airborne synthetic aperture radar and its application. In April 2008 the 20th anniversary of the maiden flight of the well-known E-SAR system was celebrated. E-SAR has been maintained well over the time. It provided valuable knowledge to the science community, especially in the past 10 years. However, it became more and more obvious that a technological renewal was inevitable. Consequently the development of a new SAR system was put on line under the name `F-SAR'.

A simple vegetation model for polarimetric covariance and coherency matrix elements is presented. The model aims to represent vegetation characteristics which are observable by radar polarimetry, including the average particle scattering anisotropy, the main orientation of the volume, the degree of orientation randomness in the volume, and the terrain slopes. The goal of this approach is to quantify these parameters and to enable their estimation in a remote sensing parameter inversion framework. The retrieval of parameters related to effective particle shapes in the polarization plane and the orientation distribution characteristics is evaluated on real SAR data acquired by DLR's E-SAR system at L-band.

This paper concerns forest parameter retrieval from multi - temporal polarimetric interferometric SAR data. A two - component polarimetric interferometric model, designed for geophysical parameter retrieval, is presented for volumetric media over the ground. It is founded on a scattering model based polarimetric decomposition and the random volume over ground (RVoG) PolInSAR inversion technique. For forest vegetation observed at L-band, this model accounts for the ground topography, canopy layer and total tree heights, mean wave attenuation in the canopy, tree morphology in the form of orientation distribution and effective shapes of the branches, surface scattering contribution, and double - bounce ground-trunk interactions. A parameter retrieval framework is developed for repeat-pass acquisitions which aims to estimate and to compensate temporal decorrelation. The parameter estimation performance is evaluated on real airborne L-band SAR data in the repeat pass mode.

The study of data acquired over a circular trajectory has raised an increasing interest in the SAR community. Two main reasons summarize the interest in such geometry. First, sub-wavelength resolution can be achieved, as the targets in the spotted area are observed under a 360oaperture. Second, the use of the information from different azimuthal directions allows one to obtain information of the scene in the third dimension, making possible a 3D target reconstruction. In any case, both applications require certain target reflectivity homogeneity. This paper shows several processing results and analyzes the potentials and limitations of circular SAR to perform tomography of semi-transparent media. Special processing aspects, like the estimation of residual motion errors due to inaccuracies in the navigation data, are also addressed. Data acquired at L-band by DLR's E-SAR system are used to demonstrate the high resolution and tomographic imaging capabilities of circular SAR. The results include the tomogram of a Luneburg lens, as well as preliminary results over man-made targets and vegetation.

In SAR tomography, the available information in the height direction is limited by the number of different tracks that can be acquired in practice. To counterbalance this limitation, electromagnetic scattering models, properly exploiting the available a priori information, should be used, the ¿few¿ possible acquisitions should be accurately selected, and processing algorithms, guaranteeing the reliability of the results, should be employed. We present an approach for the reconstruction of the vertical reflectivity distribution of vegetated areas facing the above three points. In particular, an eigenvalue optimization procedure is exploited to design an ¿optimal¿ constellation to be flown, the peculiar features of ground and canopy are accounted for and an effective global optimization algorithm is used to enhance the reliability. The approach is tested with both simulated and real data acquired by the E-SAR system of DLR over the Dornstetten forest test-site.

This letter generalizes a multibaseline interferometric synthetic aperture radar (InSAR) signal model to the polarimetric scenario. Based on this formulation, two high-performance spectral analysis techniques are adapted to process multibaseline Pol-InSAR observations. These new methods enhance the height estimation of scatterers by calculating optimal polarization combinations and allow the determination of their physical characteristics. Applying the proposed algorithms to urban environments, the building layover problem is analyzed by means of polarimetric dual-baseline InSAR measurements: the ground and building height are estimated. The techniques are validated using dual-baseline Pol-InSAR data acquired by DLR's Experimental SAR (E-SAR) system over Dresden city.

The performance of a tracking algorithm considering remotely sensed data strongly depends on a correct statistical description of the data, i.e., its noise model. The objective of this paper is to introduce a new intensity tracking algorithm for synthetic aperture radar (SAR) data, considering its multiplicative speckle/noise model. The proposed tracking algorithm is discussed regarding the measurement of glacier velocities. Glacier monitoring exhibits complex spatial and temporal dynamics including snowfall, melting, and ice flows at a variety of spatial and temporal scales. Due to these complex characteristics, most traditional methods based on SAR suffer from speckle decorrelation that results in a low signal-to-noise ratio. The proposed tracking technique improves the accuracy of the classical intensity tracking technique by making use of the temporal speckle structure. Even though a new intensity-based matching algorithm is proposed, particularly for incoherent data sets, the analysis of the proposed technique was also performed for correlated data sets. As it is demonstrated, the velocity monitoring can be continuously performed by using the maximum likelihood (ML) texture tracking without any assumption concerning the correlation of the data set. The ML texture tracking approach was tested on ENVISAT-ASAR data acquired during summer 2004 over the Inyltshik glacier in Kyrgyzstan, representing one of the largest alpine glacier systems of the world. It will be demonstrated that the proposed technique is capable of robustly and precisely detecting the surface velocity field and velocity changes in time.

This paper presents a methodology to process airborne interferometric synthetic aperture radar (SAR) data to measure surface velocity fields (SVFs) of temperate glaciers, and applies it to data acquired over the Aletsch glacier. The first part of this paper deals with the main limitation in airborne interferometric SAR to retrieve reliable interferometric products, namely, the existence of the so-called residual motion errors - inaccuracies on the order of a few centimeters in the navigation system. An extended multisquint approach is proposed for their estimation in the case of nonstationary scenes. The second part of this paper expounds an efficient methodology to derive SVFs with airborne systems, where the line-of-sight displacement is estimated using differential interferometry and the along-track component by estimating the azimuth coregistration offsets. The necessary steps to finally obtain the 3-D SVF are also presented, as well as the possibility of combining different acquisition geometries. Airborne interferometric SAR data acquired by the Experimental SAR system of the German aerospace center over the Aletsch glacier, located in the Swiss Alps, are used to evaluate the performance of the proposed approach. The motion of the corner reflectors deployed in the scene is retrieved with an accuracy between 1 and 5 cm/day using L-band data.

This paper focuses on the physical understanding of the polarimetric interferometric SAR (PolInSAR) coherence, and on the accurate utilization of this coherence for vegetation parameter inversion. A polarimetric interferometric vegetation model presented here provides the possibility to estimate parameters related to ground topography, vegetation, and surface scattering. In particular, one can estimate such vegetation characteristics as the main orientation, the degree of orientation randomness and the effective shape of the particles, together with structural parameters like the ground height and the depths of vegetation layers. The polarimetric model is based on the Freeman's three component decomposition, which is extended to consider vegetation orientation. To enhance polarimetry, a complimentary interferometric coherence model is presented. The model and the parameter inversion method are tested on accurate electromagnetic simulations of real forests. Parameter inversion performance is evaluated for single-baseline and multibaseline data.

Modern space-borne SAR sensors, like ALOS-PALSAR, TerraSAR-X and Radarsat-2 all provide at least a "partial polarimetric mode", acquiring only 2 of the 4 elements of the Sinclair matrix, like for example HH and HV or VV and VH. In addition, it has been demonstrated that with certain so-called "compact PolSAR" single-transmit dual-receive techniques one can obtain an estimation of the fully polarimetric information. Such systems are attractive in terms of reduction of pulse repetition frequency, data rate, and complexity and are currently very popular. However, they do not acquire complete information pertaining to the full polarisation state of the target and, as a consequence also coherence optimisation suffers from the reduced configuration space. In this paper, the potential of the different partial polarimetric setups for coherence optimisation is evaluated both theoretically and experimentally and compared to the capabilities of a fully polarimetric system. It will be analysed to which extent partial polarimetric system can improve the derivation of interferometric information from partly decorrelated surfaces, in particular of vegetated or even forested areas. Special attention is paid to the constrained coherence optimisation of multi-baseline setups, important for modern DInSAR techniques like PS analysis and continuous DInSAR monitoring in general. All experimental analyses will be performed using fully polarimetric multi-baseline data sets. For proper comparison, partial polarimetric information is derived from these by matrix transformations according to the respective transmit / receive configuration.

This paper generalizes a multibaseline interferometric SAR signal model to the polarimetric configuration. Based on this formulation, two high-performance array signal processing techniques are adapted to analyze multibaseline POL-InSAR observations. These new methods enhance the height estimation of scatterers by calculating optimal polarization combinations and allow the determination of their physical characteristics. Applying the algorithms to urban environments, the building layover problem is resolved by means of polarimetric dual-baseline InSAR measurements: Up to two components within one azimuth-range resolution cell are separated. The techniques are tested using dual-baseline Pol-InSAR data acquired by DLR's E-SAR system over Dresden city.

This letter analyzes different approaches for polarimetric optimization of multibaseline (MB) interferometric coherences. Two general methods are developed to simultaneously optimize coherences for more than two data sets. The first method provides every data set with a distinct dominant scattering mechanism (SM). The second optimization method is constrained to use equal SMs at all data sets. As the experimental results indicate, MB coherence optimization does improve the accuracy in the estimation of dominant SMs and the associated interferometric phases. Both methods are evaluated on real data acquired by the German Aerospace Agency (DLR)'s enhanced synthetic aperture radar sensor (ESAR) at L-band.

This paper presents airborne differential synthetic aperture radar (SAR) interferometry results using a stack of 14 images, which were acquired by the Experimental SAR system of the German Aerospace Center (DLR) during a time span of 2.5 h. An advanced differential technique is used to retrieve the error in the digital elevation model and the temporal evolution of the deformation for every coherent pixel in the image. The two main limitations in airborne SAR processing are analyzed, namely, the existence of residual motion errors (RMEs) (inaccuracies in the navigation system on the order of 1-5 cm) and the accommodation of the topography and the aperture dependence on motion errors during the processing. The coupling between them is also addressed, showing that the estimation of the differential RME, i.e., baseline error, can be biased when using techniques based on the coregistration between interferometric looks. The SAR focusing chain to process the data is also presented together with the modifications in the differential interferometry processor to deal with the remaining baseline error. The detected motion of a corner reflector and the measured deformation in several agricultural fields allows one to validate the proposed techniques.

A grown importance in long-term operational glacier monitoring has emerged, mainly due to the connection of glacier recession to climate changes. Up to now, mainly two types of methods have been used for the estimation of glacier flow velocities: Image matching and differential interferometry (DInSAR). Although the principal potential of DInSAR for glacier velocity estimation has been shown in several case studies, its successful application is often limited by phase noise, described by the coherence. Additionally, the glacier velocity is often too large to be analysed by means of DInSAR since this method can be too sensitive to correctly track the large displacements occurring during a typical data acquisition interval of one month. SAR amplitude images are not limited by phase stability problems like in DInSAR and can reliably be acquired on a regular basis. In this work, a novel algorithm for computing the velocity field and motion parameters from a sequence of SAR amplitude images are presented. The algorithm is based on the vector relaxation combined with standardized cross- covariance matrix information and cross-correlation techniques. The cross-correlation is used to indicate the candidate motion vectors for each pixel. After this step, by a relaxation operation local smoothness constraints are introduced into the estimated flow pattern, leading to a more homogeneous velocity estimation. In order to handle fast motion and reduce the mismatches, the mentioned algorithms are applied in different scales and linked using anisotropic diffusion equation in case of multiscale cross-correlation. This significantly improves the reliability of the motion detection in the presence of noise, inherent in case of SAR data.

This article presents a statistical approach for the study of PolSAR images using Time-Frequency (TF) correlation properties. PolSAR information is analyzed using a linear time- frequency (TF) decomposition which permits to describe a scene polarimetric behavior for different azimuth angles of observation and frequencies of illumination. A TF signal model is proposed and studied using two statistical descriptors related to the signal stationary aspect and coherence in the time-frequency domain. These indicators are shown to provide complementary information for an enhanced description of the scene.

The paper presents a new framework for the classification of polarimetric SAR data. The underlying model introduces cyclic conditional dependencies among the class labels assigned to neighboring observations as a mechanism to regulate the spatial homogeneity of classification results. Classification is posed as an inference problem, and is solved by coherently integrating expectation maximization and graph cut optimization. Results based on real SAR data are presented.

This paper analyzes a POLInSAR coherence model with respect to polarization diversity. The coherence constituents are identified and examined. Extending POLInSAR to multiple baselines, two general multibaseline coherence optimization methods are introduced. The coherence model is utilized to discuss the advantages and applications of these newly developed multibaseline coherence optimization methods.

This paper deals with the methodology in the processing of airborne SAR data to measure glacier displacement fields. The possibility to retrieve a 2D displacement map of the deformation in slant-range geometry with an airborne platform is discussed. A new extended multisquint approach is proposed to simultaneously estimate residual motion errors and the along-track displacement of the glacier, while the across-track displacement is obtained by means of differential interferomatry. Experimental results are shown with data acquired by the Experimental SAR (E-SAR) of the German Aerospace Center over the Aletsch glacier in the Swiss Alps.

This paper presents airborne differential SAR results using a stack of 14 images, which were acquired by the experimental SAR (E-SAR) system of the German Aerospace Center during a time span of only two and a half hours. An advanced differential technique is used to retrieve the error in the digital elevation model and the temporal evolution of the deformation for every coherent pixel in the image. The two main limitations in airborne SAR processing are analyzed, namely the existence of residual motion errors (inaccuracies in the navigation system in the order of 1-5 cm), and the accommodation of the topography and the aperture during processing. The SAR focusing chain to process the data is also presented, together with the modifications in the differential processor to deal with the remaining baseline error. The detected deformation of a corner reflector and of several agricultural fields allows validating the proposed techniques.

This paper presents a distributed approach for time- domain focusing, which significantly enhances the overall efficiency by distributing the computational load across a (potentially large) number of networked computers. The system described includes the so-called master, responsible for pre-processing, the distribution of fragments of raw-data data and the collection of processed image fragments. Fragments of raw-data are passed to so-called slaves, any number of which can be connected to the master, which are responsible for the focusing itself. Master and slave actively communicate over the network to organise the entire process in a scalable manner. In this way, time-domain processing can be accelerated by a factor that is virtually linear in the number of participating slaves. This paper summarises the current status of software development, realised in a platform-independent way using the IDL and Java languages. Additionally, some preliminary evaluations of performance, scalability and the required network infrastructure are given. Some examples of SAR data, acquired by the airborne sensor E-SAR of DLR, and processed with the system described are shown.

An interesting, but rarely used technique in polarimetric SAR interferometry is the enhancement of interferometric coherence by projection into an optimal polarimetric state. In particular, newly developed methods for polarimetric optimisation of multi-baseline coherences provide the possibility of simultaneous constrained coherence optimisation for more than one baseline. This technique can significantly improve the usefulness of long-term interferometric pairs and time-series, and appears, therefore, of interest to various fields of application. The aim of this paper is to discuss the correct derivation of multi-baseline differential interferograms with polarimetrically optimised coherence and to outline several possible areas of application, particularly in the field of differential interferometry and permanent scatterers.

This paper generalizes a multibaseline interferometric SAR signal model taking polarization diversity into account. Based on this formulation, two high-performance spectral analysis techniques are extended to the multibaseline POL-InSAR configuration. These new algorithms enhance the height estimation of scatterers by calculating optimal polarization combinations and allow to determine their physical characteristics. Applying the methods to urban scenes, experimental results show the retrieval of building height and polarimetric properties by means of single-baseline polarimetric datasets. Dual-baseline observations permit the solution of the layover problem by separating two contributions within one resolution cell. The algorithms are tested using multibaseline Pol-InSAR data acquired by DLR's E-SAR system over Dresden city.

Estimating the number of backscattering sources is an important issue in analyzing multibaseline interferometric SAR data. This paper extends model order selection algorithms to process polarimetric multibaseline InSAR observations. These methods are applied to urban environments using fully polarimetiric dual-baseline InSAR data of Dresden city acquired by DLR's E-SAR system. Experimental results for single polarization and polarimetric set-ups are presented and discussed.

This letter presents a comparison between three Fourier-based motion compensation (MoCo) algorithms for airborne synthetic aperture radar (SAR) systems. These algorithms circumvent the limitations of conventional MoCo, namely the assumption of a reference height and the beam-center approximation. All these approaches rely on the inherent time–frequency relation in SAR systems but exploit it differently, with the consequent differences in accuracy and computational burden. After a brief overview of the three approaches, the performance of each algorithm is analyzed with respect to azimuthal topography accommodation, angle accommodation, and maximum frequency of track deviations with which the algorithm can cope. Also, an analysis on the computational complexity is presented. Quantitative results are shown using real data acquired by the Experimental SAR system of the German Aerospace Center (DLR).

This paper describes an unsupervised classifier for polarimetric interferometric synthetic aperture radar (PolInSAR) data. Expectation maximization is used to estimate class parameters that maximize the likelihood of observations in an input data set for a given number of classes. Polarimetric information, in the form of coherency matrices, and interferometric information, in the form of complex coherences, are taken into account. Differences in interferometric phase across different polarization states are explicitly modeled to make the classifier sensitive to the vertical structure of the scene under observation, and the distribution over such phase differences is introduced. The classifier is self-initializing, in that it does not rely on decompositions or thresholds. Classification results obtained for real polarimetric interferometric data are presented and discussed.

This paper presents airborne DInSAR results using a stack of 14 images, which were acquired by the Experimental SAR (E-SAR) system of the German Aerospace Center (DLR) during a time span of only three hours and fifteen minutes. An advanced differential technique is used to retrieve the error in the digital elevation model (DEM) and the temporal evolution of the deformation for every coherent pixel in the image. Furthermore, some modifications in the differential processing chain are included to deal with the existence of the so-called residual motion errors, which play a similar role as atmospheric artifacts in the spaceborne case. The detected deformation of a corner reflector and of some agricultural fields allows to validate the proposed techniques to measure deformation phenomena with an airborne platform.

This letter proposes an algorithm to improve the range resolution in airborne synthetic aperture radar (SAR) data by coherently combining an interferometric image pair, i.e., two images acquired with slightly different viewing angles. This algorithm is based on the wavenumber shift principle. In contrast to other methods, developed for application to spaceborne SAR data, the proposed algorithm takes the nonlinear effects due the strong variations in incidence angle in airborne SAR data into account. The proposed method is applied to SAR data of German Aerospace Center (DLR)'s E-SAR sensor. Quantitative verification results are obtained by measuring the resolution of several corner reflectors placed in the area under study, as well as the resolution of speckle of different areas. It is demonstrated that a resolution improvement of almost a factor of two can be achieved by incorporating a second interferometric image, which can be acquired easily with an airborne sensor.

The processing of airborne synthetic aperture radar (SAR) data requires a precise compensation of the deviations of the platform movement from a straight line. This is usually carried out by recording the trajectory with a high-precision navigation system and correcting them during SAR focusing. However, due to the lack of accuracy in current navigation systems, residual motion errors persist in the images. Such residual motion errors are mainly noticeable in repeat-pass systems, where they are causing time-varying baseline errors, visible as artefacts in the derived phase maps. In this letter, a refined method for the estimation of time-varying baseline errors is presented. An improved multisquint processing approach is used for obtaining robust estimates of higher order baseline errors over the entire scene, even if parts of the scene are heavily decorrelated. In a subsequent step, the proposed method incorporates an external digital elevation model for detection of linear and constant components of the baseline error along azimuth. Calibration targets in the scene are not necessary.

This paper presents the first step to characterisescatterers using polarimetric SAR tomography (POLTOMSAR).It is a logical extension of the tomographic data processing, whichconsists to use the vectorial properties of electromagnetic waves.An introduction to the estimation of the polarisation state ofretrieved target is proposed. It is based on a modified signalmodel adapted to the MUSIC algorithm. This makes it possibleto determinate the physical nature of detected object, which is notpossible using classical approach, unless having the ground-truthof the scene under study. The experimental results are shownusing a multibaseline data set acquired in L-band by DLR’sexperimental SAR (E-SAR) on a test site near Oberpfaffenhofen/ Germany.

This paper presents a first evaluation of the ESPRIT approach in polarimetric interferometric SAR. This evaluation is carried out by using 3D images obtained by SAR tomographic like an alternative to the acquisition of ground-truth data, which is an extremely complex task in the case of volume areas. All parameters over a volumetric area are directly visible in a tomographic image and can, therefore, be employed to validate the ESPRIT approach by comparing parameters generated by ESPRIT and the SAR tomography approach. This allows to identify the principal deficiencies of the ESPRIT method, which occur over high vegetation areas, where there is a misinterpretation of the ESPRIT results. Whereas, the ESPRIT approach is useful for building characterisation, identifying a good applicability area. Airborne L-band repeat-pass interferometric data of the German Aerospace Center (DLR) experimental airborne SAR are used to perform this evaluation.

This paper presents a new motion compensation algorithm to process airborne interferometric repeat-pass SAR data. It accommodates topography variations during SAR data processing, using an external digital elevation model. The proposed approach avoids phase artifacts, azimuth coregistration errors and impulse response degradation, which usually appear due to the assumption of a constant reference height during motion compensation. It accurately modifies phase history of all targets before azimuth compression, resulting in an enhanced image quality. Airborne L-band repeat-pass interferometric data of the German Aerospace Center (DLR) experimental airborne SAR (E-SAR) are used to validate the algorithm.

This letter proposes a building characterization technique for L-band polarimetric interferometric synthetic aperture radar (SAR) data. This characterization consists of building identification and height estimation. Initially, a polarimetric interferometric segmentation is performed to isolate buildings from their surroundings. This classification identifies three basic categories: single bounce, double bounce, and volume diffusion. In order to compensate for the misclassifications among the volume and the double-bounce classes, interferometric phases given by the high-resolution Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) method are analyzed. Once buildings are localized, a phase-to-height procedure is applied to retrieve building height information. The method is validated using E-SAR, German Aerospace Center (DLR) fully polarimetric SAR data, at L-band, repeat-pass mode, over the Oberpfaffenhofen, Germany, test site, with a spatial resolution of 1.5 m in range and azimuth. More than 80% of buildings are retrieved with acceptably accurate height estimates.

This letter presents a new motion compensation algorithm to process airborne interferometric repeat-pass synthetic aperture radar (SAR) data. It accommodates topography variations during SAR data processing, using an external digital elevation model. The proposed approach avoids phase artifacts, azimuth coregistration errors, and impulse response degradation, which usually appear due to the assumption of a constant reference height during motion compensation. It accurately modifies phase history of all targets before azimuth compression, resulting in an enhanced image quality. Airborne L-band repeat-pass interferometric data of the German Aerospace Center experimental airborne SAR (E-SAR) is used to validate the algorithm.

Radio interferences are becoming more and more an important source for image degradation in synthetic aperture radar (SAR) imaging. Especially at longer wavelengths, interferences are often very strong, and their suppression is required during data processing. However, at shorter wavelengths, interferences are often not obvious in the image amplitude, and filtering is not performed in an operational way. Nevertheless, interferences might significantly degrade the image phase, and the estimation of sensitive parameters like interferometric coherence or polarimetric descriptors becomes imprecise. Interference suppression is usually performed on the raw data, which are in most cases not available to the end-user. In this letter, a new interference suppression method for focused SAR images is proposed. Its performance is tested on interferometric repeat-pass data acquired by the German Aerospace Agency's experimental SAR system (E-SAR) at L-band.

This paper discusses the detection and correction of residual motion errors in airborne SAR interferograms. They usually appear due to the lack of precision in the navigation system. Two techniques existing in the literature to detect such errors are presented, highlighting differences and similarities. The effects of residual motion errors in the final interferogram are mainly two: azimuth phase undulations and azimuth registration errors. A new correction approach is proposed, which corrects both effects in one step, avoiding the use of interpolations. Additionally, the spectral diversity technique, used to estimate registration errors, is critically analyzed. Airborne L-band repeat-pass interferometric data of the German Aerospace Center (DLR) experimental airborne SAR (E-SAR) is used to validate the method.

This letter discusses the detection and correction of residual motion errors that appear in airborne synthetic aperture radar (SAR) interferograms due to the lack of precision in the navigation system. As it is shown, the effect of this lack of precision is twofold: azimuth registration errors and phase azimuth undulations. Up to now, the correction of the former was carried out by estimating the registration error and interpolating, while the latter was based on the estimation of the phase azimuth undulations to compensate the phase of the computed interferogram. In this letter, a new correction method is proposed, which avoids the interpolation step and corrects at the same time the azimuth phase undulations. Additionally, the spectral diversity technique, used to estimate registration errors, is critically analyzed. Airborne L-band repeat-pass interferometric data of the German Aerospace Center (DLR) experimental airborne SAR is used to validate the method.

In this overview, reasons are provided on why we do need to place multi-modal, multi-band single and multiple pass POLinSAR monitoring platforms into air and space. The questions "on what POLinSAR monitoring can provide that POL-SAR and IN-SAR by themselves cannot accomplish" is assessed; whereupon facts and justifications on placing POL-IN-BISAR satellite clusters into space are presented. Reasons for this technology becoming a basic requirement for current, near-future and much more so for future all day & night year-round monitoring of the terrestrial covers are analyzed in view of the un-abating and uncontrollable terrestrial population explosion, which has, does and for ever will result in unavoidable conflicts deteriorating unfortunately at times into terrorism. The pertinent questions on how to reduce the exorbitant cost for initiating this "home-globe security protection" technology are therefore also broached, and the expected benefits are laid out. The pertinent National and International airborne and space borne multi-modal, multi-band SAR remote sensing and security conflict surveillance support agencies are herewith invited for co-sponsoring our proposal, which is timely and fleets of orbiting multi-band POLinSAR platforms are urgently required to be placed into space.

In this paper, a fully polarimetric analysis method is introduced to decompose synthesized interferometric SAR images into sub-aperture data sets, which correspond to the scene responses under different azimuthal look-angles. A statistical analysis of polarimetric parameters permits to clearly discriminate media showing a nonstationary polarimetric behavior during the SAR integration. A method is proposed to observe the polarimetric interferometric properties of anisotropic targets.

In this paper, a fully polarimetric analysis method is introduced to decompose synthesized polarimetric images into sub-aperture data sets, which corresponds to the scene responses under different azimuthal look-angles. A statistical analysis of polarimetric parameters permits to clearly discriminate media showing a non-stationary behavior during the SAR integration. A method is proposed, which eliminates the influence of azimuthal backscattering variations in conventional polarimetric SAR data analysis.

Abstract—This paper describes the analysis of built-up areas using fully polarimetric interferometric SAR data at L-band. This approach uses a polarimetric interferometric segmentation to determine the number of dominant scattering mechanisms required by an interferometric phase estimation using ESPRIT method. I.

Abstract—In the recent years there has been growing interest in exploiting multibaseline (MB) SAR interferometry in a tomographic framework, to produce full 3D imaging e.g. of forest layers. However, Fourier-based MB SAR tomography is generally affected by unsatisfactory imaging quality due to a typically low number of baselines and their irregular distribution. In this work, we apply the more modern adaptive Capon spectral estimator to the vertical image reconstruction problem, using real airborne MB data. A first demonstration of possible imaging enhancement in real-world conditions is given. Keywords- synthetic aperture radar interferometry, electromagnetic tomography, forestry, spectral analysis. I.

In this paper a new SAR data processing algorithm denoted with Extended Omega-K (EOK) is analytically presented and formulated. EOK algorithm combines the advantages of the high accurate focusing of the wavenumber domain algorithms with high precision motion compensation. The new EOK algorithm integrates a two-step range adaptive motion compensation correction in the general formulation of the wavenumber domain algorithm, leading to a new SAR processing scheme, which is much more robust concerning long synthetic apertures and squint angle than for example the chirp-scaling method. Additionally it offers the possibility of processing wideband low-frequency airborne SAR data up to near-wavelength resolution. The performance and the accuracy of the new EOK SAR data processing algorithm is demonstrated using simulated data.

Differential interferometry using space-borne SAR sensors has become an established technique for detecting and monitoring centimetre-scale deformations of the Earth's surface, as well as glacier flows and land slides. Although often very efficient, the use of space-borne SAR data has several drawbacks, namely phase artifacts caused by atmospheric effects and very low coherence due to long data acquisition intervals. Airborne sensors on the other hand may overcome most of the problems mentioned above and provide a much higher flexibility in sense of spatial resolution, used wavelength and data acquisition. However, the use of airborne sensors has been prevented by insufficiently accurate motion compensation of the sensor platform. In this paper, the performance and deficiencies of the different approaches for estimation of residual motion errors are compared and evaluated, in the face of their application in airborne differential SAR interferometry. Some preliminary results of airborne differential SAR interferometry, obtained using an optimised motion compensation scheme, will also be shown. The analysis carried out in this paper is based on repeat-pass interferometric data acquired by DLR's experimental SAR system (E-SAR) in L-band.

In synthetic aperture radar (SAR) polarimetry, the measured polarimetric signatures are used to analyze physical scattering properties of the imaged media. It is generally assumed that the sensor has a fixed orientation with respect to the objects. However, SAR sensors operating at lower frequencies, like L- and P-band, have a wide azimuth beamwidth, i.e., during the formation of the synthetic aperture, multiple squint angles are integrated to build the full-resolution SAR image. Variations in the polarimetric properties with the azimuthal look angle remain unconsidered. In this paper, a fully polarimetric subaperture analysis method is introduced. Using deconvolution, synthesized SAR images are decomposed into subaperture datasets, which correspond to the scene responses under different azimuthal look angles. A statistical analysis of the polarimetric parameters permits to clearly discriminate media showing a nonstationary behavior during the SAR integration. Finally, a method is proposed, which eliminates the influence of azimuthal backscattering variations in conventional polarimetric SAR data analysis. The effectiveness of the new methods is demonstrated on fully polarimetric SAR data, acquired by the German Aerospace Center (DLR) airborne experimental SAR sensor (E-SAR) at L-band.

In recent years, differential interferometry using spaceborne synthetic aperture radar (SAR) sensors has become an established technique for detecting and monitoring centimetre-scale deformations of the Earth's surface, as well as glacier flows and landslides. Although often very efficient, the use of spaceborne SAR data has several drawbacks, namely phase artifacts caused by atmospheric effects and very low coherence due to long data acquisition intervals and the short radar wavelength of the sensor. Most important, current spaceborne sensors are not able to ensure flexible monitoring of critical regions. Airborne sensors may overcome most of the problems mentioned above, but up to now, the operational use of airborne differential SAR interferometry has been prevented by insufficiently accurate motion compensation of the platform. In this letter, first results of airborne differential interferometry using the German Aerospace Center (DLR) experimental SAR system (E-SAR) in the interferometric repeat-pass mode are addressed. This includes an analysis of long-term decorrelation behavior in L-band and, particularly, the correction of residual motion errors in heavily decorrelated interferograms. A first differential interferogram of agricultural and forested areas is presented and analyzed.

In this paper is introduced a fully polarimetric sub-aperture analysis method. A deconvolution technique is developed in order to decompose synthesized SAR images into sub-aperture data sets which correspond to the scene global response observed under different azimuthal look angles. A polarimetric variation analysis is achieved, using pertinent parameters, to determine the nature of the non-stationary scattering mechanisms. A statistical analysis of the polarimetric parameters permits to clearly discriminate the media showing a varying behavior during the SAR integration. Decomposition and analysis techniques are applied to data acquired by the DLR airborne E-SAR sensor at L band.

Presently, a data fusion contest is conducted to compare the potential of airborne SAR with optical sensors for mapping applications. The goal of the test is to answer two questions: (1) Can state-of-the-art airborne SAR compete with optical sensors in the mapping domain? (2) What can be gained when SAR and optical images are used in combination, i.e., when methods for information fusion are applied? The test is organized in the framework of the IEEE GRSS data fusion technical committee (DFC), ISPRS working group III/6 "Multi-Source Vision", which both have strong relations with scientists, active in research on sensor fusion and automation in mapping, and - as the provider of the main organizational framework - the European Organization for Experimental Photogrammetric Research (OEEPE), which is the European research platform of national mapping agencies and other institutions, regarding technology developments to optimize the use of core data in a geoinformation infrastructure context. In the preparatory phase of the test, which has been started on the occasion of IGARSS 2001, test data has been collected and the scope of object extraction for mapping has been defined. The outcome of this phase, i.e. the test imagery to be used in the contest and its potential for mapping is presented in this paper.

In synthetic aperture radar (SAR) interferometry, the phase differences between two different sensor positions are used to estimate the terrain topography. Although it is possible in this way to find a three-dimensional (3D) surface representation, the distribution of the different scatterers in the height direction at a fixed range and azimuth position remains unknown. Contrary to this, tomographic techniques enable a real geometric resolution capability in the height direction and introduce new possibilities for many applications and inversion problems. Even misinterpretations in SAR images caused by layover and foreshortening effects can be solved by the tomographic processing. In this paper, the successful experimental realization of polarimetric airborne SAR tomography is demonstrated for the first time. The authors present the concept of aperture synthesis for tomographic imaging for the case of a multibaseline imaging geometry and discuss the constraints arising from the limited number of flight tracks. They propose a method for reduction of the height ambiguities associated to the irregular and undersampled spatial distribution of the imaging positions. Finally, they address the experimental requirements for polarimetric airborne SAR tomography and show experimental results using a multibaseline data set acquired in L-band by DLR's experimental SAR (E-SAR) of a test-site near Oberpfaffenhofen, Germany.

This paper addresses the noise filtering problem for synthetic aperture radar (SAR) interferometric phase images. The phase noise is characterized by an additive noise model. The model is verified with an L-band shuttle imaging radar (SIR)-C interferogram. An adaptive filtering algorithm based on this noise model is developed. It emphasizes filtering noise adaptively according to the local noise level and filtering along fringes using directionally dependent windows. This algorithm is effective, especially for the tightly packed fringes of X-band interferometry. Using simulated and SIR-C/X-SAR repeat-pass generated interferograms, the effectiveness of this filter is demonstrated by its capabilities in residue reduction, adaptive noise filtering, and its ability to filter areas with high fringe rates. In addition, a scheme of incorporating this filtering algorithm in iterative phase unwrapping using a least-squares method is proposed.