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This article addresses a novel methodology for the utilization of Field Programmable Gate Array (FPGA) accelerators in on-board Synthetic Aperture Radar (SAR) processing routines. The methodology consists of using High-Level Synthesis (HLS) to create Intellectual property (IP) blocks and using the Reusable Integration Framework for FPGA Accelerators (RIFFA) to develop a Peripheral Component Interconnect express (PCIe) interface between the Central Processing Unit (CPU) and the FPGA, attaining transfer rates up to 15.7 GB/s. HLS and RIFFA reduce development time (between fivefold and tenfold) by using high-level programming languages (e.g., C/C++); moreover, HLS provides optimizations like pipeline, cyclic partition, and unroll. The proposed schematic also has the advantage of being highly flexible and scalable since the IPs can be exchanged to perform different processing routines, and since RIFFA allows employing up to five FPGAs, multiple IPs can be implemented in each FPGA. Since Fast Fourier Transform (FFT) is one of the main functions in SAR processing, we present a FPGA accelerator in charge of the reordering stage of VEC-FFT (an optimized version of FFT) as a proof of concept. Results are retrieved in reversed bit order, and the conventional reordering function may consume more than half of the total clock cycles. Next, to demonstrate flexibility, an IP for matrix transposition is implemented, another computationally expensive process in SAR due to memory access. [ABSTRACT FROM AUTHOR]

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. Index Terms--Estimation theory, glacier-motion estimation, maximum likelihood (ML) estimation, offset tracking, speckle, synthetic aperture radar (SAR).

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. Index Terms--Cryosphere, differential synthetic aperture radar (SAR) interferometry (DInSAR), SAR interferometry.

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. Index Terms--SAR polarimetry, subaperture processing, Bragg-resonance.

In recent years, differential interferometry using spaceborne synthetic aperture radar (SAR) sensors has become an established technique for detecting and monitoring centimeter-scale detbrmations of the earth's surface, as well as glacier flows and land slides. 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. Index Terms--Airborne, differential interferometry, motion errors, synthetic aperture radar (SAR).

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. Index Terms - Interferometric synthetic aperture radar (IF-SAR), phase noise filtering, phase noise modeling, phase unwrapping.

A free-floating oil spill experiment (two oil types) in the open ocean is described, and the results from slick characterization through integrated analysis of drift simulations with remote sensing and in situ data are discussed. We compare oil drift simulations (OpenOil), applying various configurations of wind, wave, and current information, with the observed slick positions and shape. We describe trajectories and dynamics of the spills, slick extent, and their evolution, and the differences in detection capabilities in optical instruments versus multifrequency PolSAR acquired by Deutsches Zentrum für Luft-und Raumfahrt F-SAR. When using the best available forcing from in situ data and forecast models, good agreement with the observed position and extent was found. A fair agreement is obtained using only numerical forecast data as input. This case study reveals that the accuracy when using modeled current is relatively higher after one full local inertial period, as the effect of incorrectly modeled amplitude of the inertial current is then vanishing. This should be a general result applicable to any oceanic drift forecast based on the modeled current. A novelty is the comparison of viscous-similar soybean and mineral oil. Our findings indicate that biological oil emulsions potentially could replace mineral oil emulsions in contingency and rehearsal campaigns, but this finding is only supported from an oil drift prediction perspective. Differences in mineral oil detection capabilities are found between synthetic aperture radar and optical imagery of thinner sheen regions. F-SAR appears to be more sensitive to thinner oil and detect a larger extent, and differences between the thinner and thicker parts are observed. [ABSTRACT FROM AUTHOR]

In this paper, a new framework for iterative speckle noise reduction in polarimetric synthetic aperture radar (SAR) data is introduced. Speckle is inherent to all coherent imaging systems and affects SAR imagery in the form of strong intensity variations in pixels with similar backscattering coefficients. This makes the interpretation of SAR data in several applications a difficult task. The proposed framework includes a preprocessing step capable of dealing with noise correlation usually found in single-look data. The general filtering approach is based on the Beltrami flow for denoising manifolds or images painted on manifolds. The principal contribution of this work is to adapt this approach to deal with covariance or coherency matrices instead of optical imagery. The evaluation presented suggests that this approach allows for good spatial and radiometric preservation compared to other state-of-the-art methods. Experiments are performed on the basis of synthetic and real-world experimental data. The validation of the proposed framework is accomplished using two refined error performance measures and the well-known effective number of looks measured. The source code of a parallel implementation of the proposed framework is released under the MPL 2.0 (https://www.mozilla.org/en-US/MPL/2.0/) alongside this paper. [ABSTRACT FROM AUTHOR]

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 (3-D) 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. We 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. We propose a method for reduction of the height ambiguities associated to the irregular and undersampled spatial distribution of the imaging positions. Finally, we 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. Index Terms--Ambiguity suppression, polarimetry and interferometry, SAR processing, synthetic aperture radar (SAR), three-dimensional (3-D) imaging, tomography.

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). [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 $15\lambda$ . Finally, we put forward a generalized range-Doppler strategy to accommodate the geometry of distributed along-track constellations in an accurate manner. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM PUBLISHER]

The global Digital Elevation Model (DEM) resulting from the TanDEM-X mission provides information about the world topography with outstanding precision. In fact, performance analysis carried out with the already available data have shown that the global product is well within the requirements of 10mabsolute vertical accuracy and 2mrelative vertical accuracy for flat to moderate terrain. The mission's science phase took place from October 2014 to December 2015. During this phase, bistatic acquisitions with across-track separation between the two satellites up to 3.6 km at the equator were commanded. Since the relative vertical accuracy of InSAR derived elevation models is, in principle, inversely proportional to the system baseline, the TanDEM-X science phase opened the doors for the generation of elevation models with improved quality with respect to the standard product. However, the interferometric processing of the largebaseline data is troublesome due to the increased volume decorrelation and very high frequency of the phase variations. Hence, in order to fully profit from the increased baseline, sophisticated algorithms for the interferometric processing, and, in particular, for the phase unwrapping have to be considered. This paper proposes a novel dual-baseline region-growing framework for the phase unwrapping of the large-baseline interferograms. Results from two experiments with data from the TanDEM-X science phase are discussed, corroborating the expected increased level of detail of the large-baseline DEMs. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 $\beta$ 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM PUBLISHER]

This letter 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 numerically computes the 2-D spectrum of a point target and then uses the transfer function of the focusing kernel to match it. The spectral support is then computed to adapt the spectrum to the output imaging geometry, so that the impulse response function (IRF) is finally obtained. The proposed approach is valid under the assumption of a large time-bandwidth product, as is usually the case for current air- and spaceborne SAR sensors. The methodology is validated by comparing the matched IRFs with the ones obtained using point-target simulations. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM PUBLISHER]

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\perp), 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. [ABSTRACT FROM PUBLISHER]

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). [ABSTRACT FROM AUTHOR]

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). [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM PUBLISHER]

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). [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM AUTHOR]

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 singleand 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. [ABSTRACT FROM AUTHOR]

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 deal with the remaining baseline error. The detected motion to of a corner reflector and the measured deformation in several agricultural fields allows one to validate the proposed techniques. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In the bistatic synthetic aperture radar (BiSAR) system, the deviation between two oscillators in different platforms will cause an additional modulation of BiSAR echoes. Therefore, phase synchronization is one of the key issues that must be addressed for the BiSAR system. The oscillator phase error model and the principle of phase synchronization are firstly described. The waveform diversity technology has been widely used in many fields, for example, the hearing aids device and the recognition of auditory input source in cocktail party problem. Inspired by this, an advanced phase synchronization scheme based on coherent integration and waveform diversity is proposed. The synchronization signal and radar signal are orthogonal signals which can be separated by using waveform diversity technique. After extracting the synchronization signal, the phase synchronization accuracy can be further improved by coherent integration. The transmission of synchronization signals between two synchronization antennas is analyzed, followed by the theoretical error analysis. Then, the processing of separating the echo signal and synchronization signal is described in detail. The simulation experiments are performed. The accuracy of phase synchronization can reach 1 degree, which verifies the effectiveness of the proposed synchronization scheme. [ABSTRACT FROM AUTHOR]

Synthetic aperture radar (SAR) tomography (TomoSAR) is a multibaseline interferometric technique that estimates the power spectrum pattern (PSP) along the perpendicular to the line-of-sight (PLOS) direction. TomoSAR achieves the separation of individual scatterers in layover areas, allowing for the 3D representation of urban zones. These scenes are typically characterized by buildings of different heights, with layover between the facades of the higher structures, the rooftop of the smaller edifices and the ground surface. Multilooking, as required by most spectral estimation techniques, reduces the azimuth-range spatial resolution, since it is accomplished through the averaging of adjacent values, e.g., via Boxcar filtering. Consequently, with the aim of avoiding the spatial mixture of sources due to multilooking, this article proposes a novel methodology to perform single-look TomoSAR over urban areas. First, a robust version of Capon is applied to focus the TomoSAR data, being robust against the rank-deficiencies of the data covariance matrices. Afterward, the recovered PSP is refined using statistical regularization, attaining resolution enhancement, suppression of artifacts and reduction of the ambiguity levels. The capabilities of the proposed methodology are demonstrated by means of strip-map airborne data of the Jet Propulsion Laboratory (JPL) and the National Aeronautics and Space Administration (NASA), acquired by the uninhabited aerial vehicle SAR (UAVSAR) system over the urban area of Munich, Germany in 2015. Making use of multipolarization data [horizontal/horizontal (HH), horizontal/vertical (HV) and vertical/vertical (VV)], a comparative analysis against popular focusing techniques for urban monitoring (i.e., matched filtering, Capon and compressive sensing (CS)) is addressed. [ABSTRACT FROM AUTHOR]

Synthetic Aperture Radar (SAR) is an established remote sensing technique that can robustly provide high-resolution imagery of the Earth's surface. However, current space-borne SAR systems are limited, as a matter of principle, in achieving high azimuth resolution and a large swath width at the same time. Digital beamforming (DBF) has been identified as a key technology for resolving this limitation and provides various other advantages, such as an improved signal-to-noise ratio (SNR) or the adaptive suppression of radio interference (RFI). Airborne SAR sensors with digital beamforming capabilities are essential tools to research and validate this important technology for later implementation on a satellite. Currently, the Microwaves and Radar Institute of the German Aerospace Center (DLR) is developing a new advanced high-resolution airborne SAR system with digital beamforming capabilities, the so-called DBFSAR, which is planned to supplement its operational F-SAR system in near future. It is operating at X-band and features 12 simultaneous receive and 4 sequential transmit channels with 1.8 GHz bandwidth each, flexible DBF antenna setups and is equipped with a high-precision navigation and positioning unit. This paper aims to present the DBFSAR sensor development, including its radar front-end, its digital back-end, the foreseen DBF antenna configuration and the intended calibration strategy. To analyse the status, performance, and calibration quality of the DBFSAR system, this paper also includes some first in-flight results in interferometric and multi-channel marine configurations. They demonstrate the excellent performance of the DBFSAR system during its first flight campaigns. [ABSTRACT FROM AUTHOR]

Digital elevation models of tidal flats are a most valuable data source for the water management of coastal areas and need frequent updates to account for changes in sedimentation, erosion and identification of damages in building infrastructure. This paper presents the conceptual design, the processing methodology and first results of an airborne SAR campaign conducted in July 2019 at the German North Sea coast, showing the potential for accurate monitoring of height changes at decimeter level in mudflat areas, as well as indication of vegetation cover and water flooded areas. [ABSTRACT FROM AUTHOR]

The paper describes a method for the accurate calibration of multi-channel SAR instruments, such as those required to support SAR polarimetry, single-pass interferometry and digital beam-forming (DBF), on the basis of dedicated SAR acquisitions containing reference targets with known properties. Unlike conventional approaches, the method is based entirely on the analysis of range-compressed raw data. It leverages the pulse-by-pulse analysis of amplitude, phase and delay variations observed within the range histories of reference targets to fully characterize and correct propagation direction dependent calibration issues such as those related to antenna pointing or antenna phase center positions. The fact that the approach does not require SAR image focusing in azimuth is especially relevant in the context of DBF, where individual channels need to be calibrated but are, by themselves, under-sampled. The calibration techniques presented are illustrated and validated using multi-channel polarimetric and single-pass interferometric SAR data acquired by DLR's airborne F-SAR and DBFSAR instruments. [ABSTRACT FROM AUTHOR]

Among the objectives of the upcoming space missions Tandem-L and BIOMASS, is the 3-D representation of the global forest structure via synthetic aperture radar (SAR) tomography (TomoSAR). To achieve such a goal, modern approaches suggest solving the TomoSAR inverse problems by exploiting polarimetric diversity and structural model properties of the different scattering mechanisms. This way, the related tomographic imaging problems are treated in descriptive regularization settings, applying modern non-parametric spatial spectral analysis (SSA) techniques. Nonetheless, the achievable resolution of the commonly performed SSA-based estimators highly depends on the span of the tomographic aperture; furthermore, irregular sampling and non-uniform constellations sacrifice the attainable resolution, introduce artifacts and increase ambiguity. Overcoming these drawbacks, in this paper, we address a new multi-stage iterative technique for feature-enhanced TomoSAR imaging that aggregates the virtual adaptive beamforming (VAB)-based SSA approach, with the wavelet domain thresholding (WDT) regularization framework, which we refer to as WAVAB (WDT-refined VAB). First, high resolution imagery is recovered applying the descriptive experiment design regularization (DEDR)-inspired reconstructive processing. Next, the additional resolution enhancement with suppression of artifacts is performed, via the WDT-based sparsity promoting refinement in the wavelet transform (WT) domain. Additionally, incorporation of the sum of Kronecker products (SKP) decomposition technique at the pre-processing stage, improves ground and canopy separation and allows for the utilization of different better adapted TomoSAR imaging techniques, on the ground and canopy structural components, separately. The feature enhancing capabilities of the novel robust WAVAB TomoSAR imaging technique are corroborated through the processing of airborne data of the German Aerospace Center (DLR), providing detailed volume height profiles reconstruction, as an alternative to the competing non-parametric SSA-based methods. [ABSTRACT FROM AUTHOR]