Accounting for relatively large seasonal and short term peatland surface vertical displacements with Synthetic Aperture Radar Interferometry (InSAR) poses a problem of possible propagation of ambiguity errors. Notwithstanding, the absence of continuous high temporal resolution peatland surface levelling measurements for validation has been something characteristic. Based on the ground levelling from a raised bog, we demonstrate the Sentinel-1 distributed scatterer (DS) time-series InSAR technique underestimates real surface displacements and hereby we question the accuracy of the approach over peatlands. When the relative surface change from 6-day interferograms is used instead of accounting for the absolute change, the estimation accuracy improves (Spearman's rho 0.82, p-value < 0.002) because 6-day in situ surface changes are usually small and do not need InSAR phase unwrapping. Despite a serious unwrapping problem in peatlands, DS time series contain useful signal and differential InSAR (DInSAR) might have potential for assessment of short term peatland surface displacements in favourable conditions.

We reveal the presence of a peculiar physical signal which compromises the accuracy of Earth surface deformation estimates for distributed scatterers [1]. The observed signal is short-lived and decays with the temporal baseline; however, it is distinct from the stochastic noise attributed to temporal decorrelation. To indicate its nature, this physical effect is referred to as fading signal. Designing a simple approach in the evaluation of distributed scatterers, we reveal a prominent bias in the deformation velocity maps. The bias is the result of propagation of small phase error through the time series. We further discuss the role of the phase estimation algorithms in significant reduction of the bias and put forward the idea of a unified analysis-ready InSAR product for achieving high-precision deformation monitoring.

This paper deals with the analysis of InSAR performance for large-scale deformation measurement. The study evaluates the use of models, especially numerical weather prediction reanalysis, to mitigate disturbances in SAR interferograms. The impact of such corrections is evaluated and, using GNSS measurements, the predicted error bars are validated on a large Sentinel-1 dataset.

This article investigates the presence of a new interferometric signal in multilooked synthetic aperture radar (SAR) interferograms that cannot be attributed to the atmospheric or Earth-surface topography changes. The observed signal is short-lived and decays with the temporal baseline; however, it is distinct from the stochastic noise attributed to temporal decorrelation. The presence of such afading signalintroduces a systematic phase component, particularly in short temporal baseline interferograms. If unattended, it biases the estimation of Earth surface deformation from SAR time series. Here, the contribution of the mentioned phase component is quantitatively assessed. The biasing impact on the deformation-signal retrieval is further evaluated. A quality measure is introduced to allow the prediction of the associated error with the fading signals. Moreover, a practical solution for the mitigation of this physical signal is discussed; special attention is paid to the efficient processing of Big Data from modern SAR missions such as Sentinel-1 and NISAR. Adopting the proposed solution, the deformation bias is shown to decrease significantly. Based on these analyses, we put forward our recommendations for efficient and accurate deformation-signal retrieval from large stacks of multilooked interferograms.

This article deals with the analysis of InSAR performance for large-scale deformation measurement. The study evaluates the use of models, especially numerical weather prediction reanalysis, to mitigate disturbances in SAR interferograms. The impact of such corrections is evaluated by analyzing short-time baseline phase variograms in order to derive a lower bound for the interferometric accuracy, especially at large distances. The variance is then propagated from single interferograms to deformation rates. Finally, using GNSS measurements, the predicted error bars are validated on a large Sentinel-1 data set.

A recent publication claims that closure phases in SAR interferometry bear no relationship to physical changes of the scatterer, but only to the statistical properties of the averaged pixels. We disprove this claim with a simple counterexample and remind the reader of cases in which closure phases indicate a clear physical content, including the exploitation of closure phases in other fields.

The presence of stochastic and systematic inconsistencies is a concern for the precision and interpretability of Interferometric Synthetic Aperture Radar (InSAR) when distributed scatterers are exploited for SAR time series analysis [1]. Multitemporal phase estimators aim at retrieving a consistent common-master interferometric time series, thereby reducing the effect of stochastic inconsistencies. Exploiting data redundancy the latter estimators are theoretically expected to decrease the susceptibility to systematic inconsistencies as well. In this contribution we seek a computationally efficient quality measure to show the effectiveness of multitemporal phase estimation in the reduction of inconsistencies. Choosing the ensemble coherence as a candidate, we firstly seek a constant false alarm rate detector for initial detection of signal-bearing areas. Furthermore the impact of phase inconsistencies on the ensemble coherence will be brought into attention.

Multitemporal phase estimation aims at the exploitation temporal data redundancy within the SAR time-series to reduce the impact of inherent stochastic and systematic interferometric phase inconsistencies [1] for distributed scatterers (DS). The consistent phase-series estimated as such is further utilized to retrieve the underlying geophysical and atmospheric signals. Therefore, the precision and interpretability of the retrieved physical signals from the DS is governed by the performance of the phase estimators. Different approaches to phase estimation calls for the investigation of their performance. Here we explain the discrepancy among the different approaches in terms of their underlying covariance model and introduce our recently proposed estimator named EMI [2]. Bridging between different approaches via revised mathematical formulation of phase estimation, EMI enhances the estimation precision and computational efficiency of the temporal phase estimation. The performance of different phase estimators is brought into attention via simulation analysis. Using Sentinel-1 time series over the North and East Anatolian Faults, wide area performance analysis is further carried out and will be presented.

Since soil moisture influences the differential interferometric synthetic aperture radar phase, it would be advantageous to be able to use InSAR to estimate the moisture. Unfortunately, it hasn't yet been demonstrated how to accomplish this in a precise and robust manner. Two major problems exist: firstly the relationship between moisture and phase variations is not yet well understood for a variety of ground covers. Secondly, various terms contribute to the interferometric phase and the soil moisture one is mostly one of the smallest, meaning that it is difficult to separate it from the other contributions and provide a reliable estimation. To address the second problem we use triplet of interferograms, canceling out all phase terms other than soil moisture. Closure phases, the triplet's product, depend on soil moisture variations with a non-linear ambiguous relationship. We show that its inversion is feasible once the ambiguity is solved. We use ALOS-2 and UAVSAR data to estimate soil moisture using a simple physical model.

The capacity of SAR interferometry to measure surface deformation with accuracy of 1 mm/year or better are well known. However this is typically limited to relative motion at short distance. Thanks to several advances in SAR sensor quality, data availability, orbit determination, processing, and calibration of atmospheric delays it is now possible to achieve that accuracy even across large distances of hundreds of kilometers.In this paper we revise the main contributions to the large scale error, considering available mitigation techniques. We provide a first validation for a processing based on Sentinel-1 data, by comparing our results with GNSS stations.For future SAR's operating at lower frequencies, it is vital to consider ionospheric corrections and likely also the influence of moisture variations in natural scatterers. The choice of processing algorithms, though typically not discussed, can also have a significant effect on the quality of the result.

This paper deals with precise absolute geolocation of point targets by means of a pair of high-resolution synthetic aperture radar (SAR) acquisitions, acquired from a satellite. Even though a single SAR image is a 2-D projection of the backscatter, some 3-D information can be extracted from a defocussing analysis, depending on the resolution, thanks to orbital curvature. A second acquisition, observing the same scene under a different look angle, adds stereogrammetric capability and can achieve geolocation accuracy at decimeter level. However, for the stereogrammetric analysis to work, it is necessary to match targets correctly in the two images. This task is particularly difficult if it has to be automatic and targets are dense. Unfortunately, the defocussing-based geolocation is not sufficient for reliable target matching: the limiting factor is the unknown tropospheric delay that can cause geolocation errors of several meters in the elevation direction. However, observing that the tropospheric phase screen displays a low-pass character, this paper shows how to identify statistically the local atmospheric disturbances, therefore dramatically improving the score of successful matching. All steps involved exploit peculiar radar image characteristics and, thanks to this, avoid generic point cloud matching algorithms. The proposed algorithm is shown at work on a pair of TerraSAR-X staring spotlight images.

Tandem-L is a proposal for an innovative L-band SAR mission for the systematic observation of dynamic processes on the Earth's surface. The mission concept is based on two SAR satellites flying in close formation featuring latest digital beamforming techniques in combination with a large deployable reflector for increasing the swath width and imaging resolution. This enables innovative operation modes such as polarimetric SAR tomography for determining the vertical structure of vegetation and ice. With novel imaging and processing techniques and the vast recording capacity of up to 8 Terabyte/day, it will provide vital information for solving pressing scientific questions in the biosphere, geosphere, cryosphere, and hydrosphere and will make an essential contribution for a better understanding of the Earth system and its dynamics. This paper gives an overview of the Tandem-L mission project which has successfully passed the intermediate system requirements review of Phase B1.

Tandem-L is a proposal for a spaceborne L-band SAR mission for the systematic observation of dynamic processes on the Earth's surface with hitherto unparalleled quality and resolution. The enormous amount of data to be acquired will be used to provide information concerning dynamic processes in the biosphere, geosphere, cryosphere, and hydrosphere [1]. Within the scope of this mission, several operational phases have been established and corresponding flight configurations have been designed. Subsequently an observation concept has been developed in order to fulfill all the scientific requirements. A sophisticated planning and optimization process has been implemented. It combines the predetermined satellite resources, ground station network, and the scientific requirements to generate an acquisition timeline on individual data take level. The resulting timeline fulfills all requirements for the various scientific applications and can be used to analyze different aspects of the mission like data volumes and orbit usage.

Signal decorrelation poses a limitation to multipass SAR interferometry. In pursuit of overcoming this limitation to achieve high-precision deformation estimates, different techniques have been developed, with short baseline subset, SqueeSAR, and CAESAR as the overarching schemes. These different analysis approaches raise the question of their efficiency and limitation in phase and consequently deformation estimation. This contribution first addresses this question and then proposes a new estimator with improved performance, called Eigendecomposition-based Maximum-likelihood-estimator of Interferometric phase (EMI). The proposed estimator combines the advantages of the state-of-the-art techniques. Identical to CAESAR, EMI is solved using eigendecomposition; it is therefore computationally efficient and straightforward in implementation. Similar to SqueeSAR, EMI is a maximum-likelihood-estimator; hence, it retains estimation efficiency. The computational and estimation efficiency of EMI renders it as an optimum choice for phase estimation. A further marriage of EMI with the proposed Sequential Estimator by Ansari et al. provides an efficient processing scheme tailored to the analysis of Big InSAR Data. EMI is formulated and verified in relation to the state-of-the-art approaches via mathematical formulation, simulation analysis, and experiments with time series of Sentinel-1 data over the volcanic island of Vulcano, Italy.

This paper addresses the performance in the retrieval of 3-D mean deformation maps by exploiting simultaneous or quasi-simultaneous squinted synthetic aperture radar (SAR) interferometric acquisitions in a repeat-pass scenario. In multisatellite or multibeam low earth observation missions, the availability of two (or more) lines of sight (LOSs) allows the simultaneous acquisition of SAR images with different squint angles, hence improving the sensitivity to the north-south component of the deformation. Due to the simultaneity of the acquisitions, the troposphere will be highly correlated and, therefore, will tend to cancel out when performing the differential measurement between the interferograms obtained with the different LOSs, hence resulting in a practically troposphere-free estimation of the along-track deformation measurement. In practice, however, the atmospheric noise in the differential measurement will increase for increasing angular separations. This paper expounds the mathematical framework to derive the performance by properly considering the correlation of the atmospheric delays between the simultaneous acquisitions. To that aim, the hybrid Cramér-Rao bound is exploited making use of the autocorrelation function of the troposphere. Some performance examples are presented in the frame of future spaceborne SAR missions at C and L band.

Wide-swath satellite missions with short revisit times, such as Sentinel-1 and the planned NISAR and Tandem-L, provide an unprecedented wealth of interferometric time series and open new opportunities for systematic monitoring of the Earth surface. The processing of the emerging Big Data with the state-of-the-art InSAR time series analysis techniques is, however, challenging. This contribution introduces a novel approach, named Sequential Estimator, for efficient estimation of the interferometric phase from the long InSAR time series. The algorithm uses recursive estimation and analysis of the data covariance matrix via division of the data into small batches, followed by compression of the data batches. From each compressed data batch artificial interferograms are formed, resulting in a strong data reduction. This scheme avoids the necessity of re-processing the entire data stack at the face of each new acquisition. It is shown that the proposed estimator introduces negligible degradation compared to the Cramér-Rao Lower Bound. The estimator may therefore be adapted for high-precision Near-Real-Time processing of InSAR and accommodate the conversion of InSAR from an off-line to a monitoring geodetic tool. The performance of the Sequential Estimator is compared to the state-of-the-art techniques via simulations and application to Sentinel-1 data.

The coregistration of synthetic aperture radar images is of fundamental importance for the generation of interferograms. The high azimuth coregistration requirements imposed by the TOPS acquisition mode imply that an advanced approach for the coregistration of stacked time series images is needed due to temporal decorrelation effects. In some scenarios, the conventional approach of estimating the shifts pairwise with respect to the same master might result insufficient. Therefore, a joint estimation is proposed here, which exploits jointly all interferograms in order to retrieve more accurate results. Simulated data and Sentinel-1A images acquired in IW mode are used to validate this procedure, demonstrating the better performance of the joint approach when compared to the standard single-master approach.

Wide-swath synthetic aperture radar (SAR) missions with short revisit times, such as Sentinel-1 and the planned NISAR and Tandem-L, provide an unprecedented wealth of interferometric SAR (InSAR) time series. However, the processing of the emerging Big Data is challenging for state-of-the-art InSAR analysis techniques. This contribution introduces a novel approach, named Sequential Estimator, for efficient estimation of the interferometric phase from long InSAR time series. The algorithm uses recursive estimation and analysis of the data covariance matrix via division of the data into small batches, followed by the compression of the data batches. From each compressed data batch artificial interferograms are formed, resulting in a strong data reduction. Such interferograms are used to link the “older” data batches with the most recent acquisitions and thus to reconstruct the phase time series. This scheme avoids the necessity of reprocessing the entire data stack at the face of each new acquisition. The proposed estimator introduces negligible degradation compared to the Cramer-Rao lower bound under realistic coherence scenarios. The estimator may therefore be adapted for high-precision near-real-time processing of InSAR and accommodate the conversion of InSAR from an offline to a monitoring geodetic tool. The performance of the Sequential Estimator is compared to state-of-the-art techniques via simulations and application to Sentinel-1 data.

Variations of the ionosphere can significantly disrupt synthetic aperture radar (SAR) acquisitions and interferometric measurements of ground deformation. In this paper, we show how the ionosphere can also strongly modify C-band interferograms despite its smaller influence at higher frequencies. Thus, ionospheric phase screens should not be neglected: their compensation improves the estimation of ground deformation maps. The split-spectrum method is able to estimate the dispersive ionospheric component of the interferometric phase; we describe the implementation of this method for the burst modes TOPS and ScanSAR to estimate and remove ionospheric phase screens. We present Sentinel-1 interferograms of the 2016 Taiwan earthquake and ALOS-2 interferograms of the 2015 Nepal earthquake, which show strong ionospheric phase gradients, and their corrected versions. Finally, to validate the results and better understand the origin of these ionospheric variations, we compare the estimated differential ionosphere with global Total Electron Content maps and local Global Positioning System measurements.

The ionospheric propagation path delay is a major error source in synthetic aperture radar (SAR) interferograms and, therefore, has to be estimated and corrected. Various methods can be used to extract different kinds of information about the ionosphere from SAR images, with different accuracies. This paper presents a general technique, based on a Bayesian inverse problem, that combines various information sources in order to increase the estimation accuracy, and thus the correction. A physically realistic fractal modeling of the ionosphere turbulence and a data-based estimation of the model parameters allow the avoidance of arbitrary filtering windows and coefficients. To test the technique, the differential ionospheric phase screen was estimated by combining the split-spectrum method with the azimuth mutual shifts between interferometric pair images. This combination is convenient since it can benefit from the strengths of both sources: range and azimuth variations from the split-spectrum method and small-scale azimuth variations from more sensitive azimuth shifts. Therefore, the two methods can recover the long and short wavelength components of the ionospheric phase screen, respectively. A theoretical comparison between the Faraday rotation method and the split-spectrum method is also reported. For the use in the combination, precedence was then given to the split-spectrum method because of the comparable precision level, lower susceptibility to biases, and wider applicability. Finally, Advanced Land Observing Satellite Phased Array type L-band SAR L-band images are used to show how the combined result is more accurate than that obtained with the simple split-spectrum method.

This paper presents a methodology to design a spaceborne dual-beam along-track synthetic aperture radar interferometer to retrieve ocean surface velocity vectors. All related aspects and necessary tradeoffs are identified and discussed or reviewed, respectively. This includes a review of the measurement principle and the relation between baseline and sensitivity, the relation between wind and radar backscatter, a discussion of the observation geometry, including the antenna concept, polarization diversity, and all main error contributions. The design methodology consists of a sensitivity-based derivation of explicit instrument requirements from scientific requirements. In turn, this derivation is based on a statistical model for the interferometric phase error. This allows a quantitative, wellgrounded instrument design offering an additional degree of freedom to the approach, which we call “noise-equivalent-sigmazero requirement space.” Crucial tradeoffs for the system design, such as the resolution, the number of independent looks, the minimum wind speed, and the coherence and ambiguities, are pointed out and discussed. Finally, this paper concludes with a single platform system concept operating in Ku-band, which provides the measurement quality needed to achieve a surface velocity estimation accuracy of 5 cm/s, 200-km swath coverage, for 4×4 km2L2-product resolution and winds starting at 3 m/s.

The launch of the wide-swath SAR missions with short repeat-pass cycles, such as Sentinel-1, will soon provide an unprecedented large InSAR data archive. Time-series analysis on the rapidly growing data will thus become computationally demanding for a systematic monitoring of earth surface deformation. As the state-of-the-art approach in differential InSAR time-series analysis, the distributed scatterer interferometric (DSI) techniques shall adapt agile processing schemes to deal with the emerging big data; an aspect to which limited attention has been dedicated. In this contribution, a sequential DSI scheme is proposed to address this demand. Based on SAR data reduction, the scheme allows for batch processing of the large data stacks while preserving the performance close to the Cramér-Rao Lower Bound. The performance of theof earth surface deformation. As the state-of-the-art approach in differential InSAR time-series analysis, the distributed scatterer interferometric (DSI) techniques shall adapt agile processing schemes to deal with the emerging big data; an aspect to which limited attention has been dedicated. In this contribution, a sequential DSI scheme is proposed to address this demand. Based on SAR data reduction, the scheme allows for batch processing of the large data stacks while preserving the performance close to the Cramér-Rao Lower Bound. The performance of the proposed sequential estimator is compared to the current DSI algorithms under two contradicting coherence scenarios. The application of the proposed sequential estimator to stacks proposed sequential estimator is compared to the current DSI algorithms under two contradicting coherence scenarios. The application of the proposed sequential estimator to stacks of Sentinel-1 data is ongoing.

This paper presents a novel approach to determine 3D absolute geolocation of point targets using just two long-aperture SAR acquisitions. Moreover, the Zenith Path Delay of both acquisitions is obtained. First results presented here show that the absolute positioning accuracy reaches the sub-meter level.

Tandem-L is a highly innovative SAR satellite mission for the global observation of dynamic processes on the Earth's surface with hitherto unknown quality and resolution. Thanks to its novel imaging techniques and its unprecedented acquisition capacity, Tandem-L will deliver urgently needed information for the solution of pressing scientific questions in the areas of the biosphere, geosphere, cryosphere and hydrosphere. The feasibility of Tandem-L has been analyzed and confirmed in the scope of a phase A study, which has been conducted in close cooperation between the German Aerospace Center (DLR) and the German space industry. This paper provides an overview of the Tandem-L mission concept and summarizes the actual development status.

Correlating SAR (CoSAR) has been recently proposed as a geosynchronous remote sensing mission capable of delivering continental coverage of ocean surfaces with a high repeat cycle. The main specific measurements provided by CoSAR are estimates of the normalised radar cross section (NRCS), Doppler shifts, and surface topography with higher resolution than microwave radiometers and larger coverage than state-of-the-art LEO SAR constellations. This paper analyses the specific geometrical characteristics of CoSAR surveys and discusses the challenges of efficient CoSAR image formation approaches. The space-variance of CoSAR surveys is expected to be small, hence CoSAR image formation can benefit from the available knowledge in efficient bistatic and multistatic SAR image formation approaches.

A conventional interferometric synthetic aperture radar (SAR) system provides 1-D line-of-sight motion measurements from repeat-pass observations. Two-dimensional motions may be measured by combining two observations from ascending and descending geometries. The third motion component may be retrieved by adding a third geometry and/or by integrating along-track measurements although with much reduced precision compared to the other two components. Several options exist to improve the accuracy of retrieving the third motion component, such as combining left- and right-looking observations or exploiting recently proposed innovative SAR acquisition modes (BiDiSAR and SuperSAR). These options are, however, challenging for future SAR systems based on large reflector antennae, due to lack of capability to electronic beam steering or frequent toggle between left- and right-looking modes. Therefore, in this letter, we assess and compare the realistic acquisition scenarios for a reflector-based SAR in an attempt to optimize the achievable 3-D precision. Investigating the squinted SAR geometry as one of the feasible scenarios, we show that a squint of 13.5° will yield comparable performance to the left-looking acquisition, while further squinting outperforms this or other feasible configurations. As an optimum configuration for 3-D retrieval, the squinted acquisition is further elaborated: the different acquisition plans considering a constellation of two satellites as well as the challenges for data processing are addressed.

The differential ionospheric path delay is a major error source in L-band interferograms. It is superimposed to topography and ground deformation signals, hindering the measurement of geophysical processes. In this paper, we proceed toward the realization of an operational processor to compensate the ionospheric effects in interferograms. The processor should be robust and accurate to meet the scientific requirements for the measurement of geophysical processes, and it should be applicable on a global scale. An implementation of the split-spectrum method, which will be one element of the processor, is presented in detail, and its performance is analyzed. The method is based on the dispersive nature of the ionosphere and separates the ionospheric component of the interferometric phase from the nondispersive component related to topography, ground motion, and tropospheric path delay. We tested the method using various Advanced Land Observing Satellite Phased-Array type L-band synthetic aperture radar interferometric pairs with different characteristics: high to low coherence, moving and nonmoving terrains, with and without topography, and different ionosphere states. Ionospheric errors of almost 1 m have been corrected to a centimeter or a millimeter level. The results show how the method is able to systematically compensate the ionospheric phase in interferograms, with the expected accuracy, and can therefore be a valid element of the operational processor.

This paper presents the correlating synthetic aperture radar (CoSAR) technique, a novel radar imaging concept to observe statistical properties of fast decorrelating surfaces. A CoSAR system consists of two radars with a relative motion in the along-track (cross-range) dimension. The spatial autocorrelation function of the scattered signal can be estimated by combining quasi-simultaneously received radar echoes. By virtue of the Van Cittert-Zernike theorem, estimates of this autocorrelation function for different relative positions can be processed by generating images of several properties of the scene, including the normalized radar cross section, Doppler velocities, and surface topography. Aside from the geometric performance, a central aspect of this paper is a theoretical derivation of the radiometric performance of CoSAR. The radiometric quality is proportional to the number of independent samples available for the estimation of the spatial correlation, and to the ratio between the CoSAR azimuth resolution and the real-aperture resolution. A CoSAR mission concept is provided where two geosynchronous radar satellites fly at opposing sides of a quasi-circular trajectory. Such a mission could provide bidaily images of the ocean backscatter, mean Doppler, and surface topography at resolutions on the order of 500 m over wide areas.

Interferometric synthetic aperture radar (InSAR) measurements are merely sensitive to the deformation along the Line of Sight (LOS) direction of the sensor. To improve the geometrical sensitivity and retrieve the three-dimensional deformation, the integration of InSAR from non-coplanar acquisitions as well as fusion with resolution-scale SAR image shift measurements has become a standard approach. Using different statistical measures, we assess and compare the influence of different image acquisition strategies as well as data fusion on the performance of InSAR in 3D deformation retrieval. Integrating nominal InSAR acquisitions, i.e. a set of measurements from ascending and descending tracks acquired from right-looking geometry, a strong correlation between the retrieved 3D parameters in the local vertical-north plane is observable. This correlation is sought to be decreased by non-nominal acquisitions; i.e. left-looking or squinted observations. These acquisition strategies are discussed for consideration in the future L-band mission Tandem-L.

Many methods, to estimate the ionospheric effects on SAR images and interferograms, have been proposed and studied in the past years. However, depending on the conditions of the ionosphere, different methods can or should be applied. The effects that an aurora event has on SAR images and inter-ferograms possibly have some differences with respect to the effects generated by a more normal ionospheric state. This work shows one of these differences, which is supposed to be a change in the ionosphere vertical profile, and propose and demonstrates a method to deal with it. This method improves the integrated-azimuth-shifts method, and permits to obtain a better estimate of the ionospheric phase screen.

This paper analyzes the impact of a spatially inhomogeneous ionosphere on spaceborne single-pass SAR interferometry. For this, linear TEC gradients and higher-order irregularities are considered. It is shown that TEC gradients as low as 0.01 TECU/km may already noticeably affect the accuracy of an L-band cross-track interferometer, causing, e.g., horizontal and vertical offsets in the order of 1-2 m. Higher-order perturbations of the electron plasma lead to additional errors that vary nonlinearly with the length of the interferometric baseline. To predict these errors, we model the ionospheric irregularities as the product of a vertical profile and a second-order stationary stochastic process with a 3-D power-law spectrum. The interferometric errors are then derived via a set of projection integrals that express the expected phase error variance as a function of the baseline length and the angular extent of the synthetic aperture. With this model, we show that the phase errors of an L-band single-pass SAR interferometer may reach several tens of degrees under medium turbulence conditions. Since these phase errors are highly correlated among neighboring resolution cells, they cannot be reduced by multi-looking, thereby posing a possible challenge for multiple baseline interferometry and SAR tomography.

This contribution reports on the performance investigations of the interferometric wide swath (IW) mode of Sentinel-1, which is implemented using the terrain observation by progressive scans (TOPS) mode. The key aspects of the TOPS mode that need to be considered for accurate interferometric processing will be presented, and first analyses with Sentinel-1 time series will be shown. The results focus on the pilot sites of Campi Flegrei/Vesuvius and Mexico City, as well as Greenland glaciers. Other aspects related to the interferometric performance are also presented, like the burst synchronization, the pointing accuracy, or the considerations when evaluating non-stationary scenes.

This contribution presents two experiments performed with the TerraSAR-X (TSX) and TanDEM-X (TDX) satellites working in the pursuit monostatic configuration. Their objective is to estimate the along-track component of the motion in the scene in repeat-pass scenarios with an accuracy better than the one given by the stripmap azimuth resolution. Such performance is possible by exploiting the angular diversity of the bidirectional (BiDi) SAR mode and the π-shifted (or staggered) TOPS.

This paper presents a spaceborne SAR mission concept in Ku-band for the measurement of the two-dimensional ocean surface current. The measurement concept is based on dual-beam along-track interferometry, which requires two highly squinted antennas each looking simultaneously in fore and aft direction. A single side-looking geometry and a ScanSAR imaging mode is chosen to complete the observational concept in order to achieve the requirements on revisit-time and coverage. The applied hybrid polarization is intended to increase the information level about different ocean scattering mechanisms. Furthermore a methodology of instrument requirement derivation is briefly discussed, ensuring the ocean current measurement accuracy requirements. Finally the instrument concept, including digital beamforming, and the SAR performance are presented.

The orbit for Earth observation satellite synthetic aperture radar (SAR) missions is maintained within an Earth-fixed orbital tube to ensure ground-track coverage repeatability and, consequently, to enable repeat-pass interferometric compatibility between data takes. In this letter, it is shown that the size of the orbital tube may affect the interferometric performance in terms of azimuth spectral decorrelation and azimuth coregistration accuracy under the presence of squint. These effects require special consideration for SAR burst modes, such as ScanSAR or TOPS (i.e., Terrain Observation by Progressive Scans). This letter presents and analyzes these aspects in the frame of the Sentinel-1 mission.

This letter discusses some aspects of the implementation of Delta-k methods for shift estimation with synthetic aperture radar images. In particular, it shows that a common Delta-k algorithm, which postpones the multilooking to the differential interferogram and is therefore robust to the presence of interferometric fringes in the averaging window, does not reach the maximum possible performance and should be better considered as a variant of incoherent cross-correlation. A small adaptation, retaining some multilooking at interferogram level, can significantly improve the efficiency.

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.

With three coherent synthetic aperture radar images, it is possible to form three interferograms. In some cases, the phases of the three averaged interferograms will be significantly inconsistent and indicate a sort of phase excess or deficit (which we call lack of triangularity or inconsistency). In this paper, we illustrate theoretically which models can explain such phenomenon and provide some real-data examples. It is also shown that two or more independent scattering mechanisms are necessary to explain phase inconsistencies. The observation of lack of consistency might be useful to derive information on the target and as a warning that the scatterer presents a temporal covariance matrix, which is not intrinsically real, with consequences for the processing of interferometric stacks.

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 letter provides a formula for the accuracy of incoherent speckle tracking (intensity cross-correlation) of homogeneous patches. The result is based on the determination of the curvature of the cross-correlation function and the noise which affects its first derivative.

This paper addresses relativistic effects in bistatic and multistatic synthetic aperture radar (SAR) systems and missions. It is shown that the use of different reference frames for bistatic SAR processing and bistatic radar synchronization is prone to notable phase and time errors. These errors are a direct consequence of the relativity of simultaneity and can be explained in good approximation within the framework of Einstein's special theory of relativity. Using the invariance of the space-time interval, an analytic expression is derived that shows that the time and phase errors increase with increasing along-track distance between the satellites. The predicted errors are in excellent agreement with measurements from TanDEM-X and provide a satisfactory explanation for previously observed digital elevation map (DEM) height offsets that exceeded ±10 m. Consideration of the unexpected relativistic effects is essential for accurate DEM generation in TanDEM-X and has in the meantime been implemented in the operational processing chain.

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.

There is a need for scattering models that link quantitatively synthetic aperture radar (SAR) interferometric observables to soil moisture. In this paper, we propose a model based on plane waves and the Born approximation, deriving first the vertical complex wavenumbers in the soil as a function of geometrical and dielectric properties and successively the complex interferometric coherences. It is observed that soil moisture behaves on the phase in a similar way as tomography does, breaking the phase consistency in triplets of interferograms. The proposed model is validated with L-band airborne SAR data; preliminary inversion results based on interferogram triplets and coherence magnitudes are presented.

Synthetic Aperture Radar (SAR) systems construct the equivalent to a very long antenna array by coherently combining radar echoes of a scene acquired along the trajectory of a space- or airborne radar. A key underlying assumption, or requirement, is that the observed scene stays coherent during the acquisition. This is true for static scenes, in particular when the acquisition time is kept short. For decorrelating targets, the azimuth resolution achievable by a SAR system is limited by the coherence time of the targets, τcoh, which limits the length of the synthetic aperture to the product of τcohand the azimuth velocity of the system. Typical cases where this can be an issue is for the observation of water surfaces, where the coherence times at microwave frequencies are typically well below 100 ms, which makes them short compared to the typically associated integration times.

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.

This letter reports about some observations over rainforests (in Brazil and Indonesia), where the spectra of TanDEM-X interferograms show distinct features, almost a signature, which is explained and modeled in terms of the scattering properties. Supported by comparisons with simulations, the observations exclude any homogeneous horizontally layered forest; instead, they are compatible with a model with point scatterers clustered in clouds. Such a model, with high extinction and large gaps that allow significant penetration, is able to explain to a good degree the observations.

In this paper a baseline (height) self-calibration concept is introduced and applied to simulations of two different single-pass interferometric SAR systems with a single-swath and a dual-swath configuration. The results will show that the general performance is very promising and that, by simultaneously acquiring two separated swathes, accuracies in the sub-decimetric range can be reached.

This paper presents the processing of TanDEM-X acquisitions for the monitoring of the topography of the Petermann ice island. In this particular case the area under study is continuously moving and the acquisition geometry is changing, so the processing of the iceberg's DEMs is challenging and additional effects are to be considered. The SAR processing chain used is presented and the results obtained summarized, showing the effects and limitations observed during the process.

This paper reports on systematic height offsets that have been observed in TanDEM-X by evaluating a large number of digital elevation model (DEM) acquisitions. Besides the expected instrument and baseline offsets, which are compensated in the calibration chain, two unexpected external error sources have been identified that apply to any formation flying bistatic SAR interferometer. The first contribution is due to relativistic effects and can be well explained within Einstein's special theory of relativity. The second effect is due to differential delays in the troposphere. It is shown that the theoretic predictions are in good agreement with the observed offsets. All necessary corrections have in the meantime been integrated in the operational TanDEM-X processing chain.

This paper provides an overview of the BIOMASS Mission End-to-End simulator (BEES) and of the mission performance analysis performed with it. The end-to-end performance, in terms of biomass estimates error, is close to the 20% error goal set for the mission. The main sources of errors are temporal decorrelation and the limited available bandwidth, while system induced errors have a negligible impact on the final performance.

This paper discusses the tomographic potential of interferometric SAR acquisitions under crossing tracks, which results from the associated baseline variation. A simple model is proposed to describe the received signal. Experimental results confirm the expected tomographic potential.

This paper presents investigations on a one year time series of crossing orbit differential interferometry SAR acquisitions with a 1-, 5- and 6-days temporal baseline. The conditions for crossing orbit interferometry are briefly discussed as the requirement of a common ground spectrum has to be satisfied. The uniquely short revisit times give the opportunity to perform interferometry on a glacier area, i.e. the Ronne ice-shelf, in X-band. The coherence results over one year as well as surface velocity measurements are shown and discussed.

This paper reports about some SAR interferometric obervations over rainforest (in Brazil and Indonesia). The spectra of TanDEM-X interferograms exhibit a bimodal character, which can be explained by the fact that vertical components of the trees are present in the interferograms. This is explained by interpreting the periodogram as a histogram of the different slopes present in the scene. Simulations based on based on clouds of point scatterers are enough for a first modeling of the observations. It is possible to show -theoretically and with the support of simulations- that a horizontally homogeneous forest model is not able to justify our observations. This analysis has been made possible by the characteristics of the TanDEM-X system: high resolution, almost no temporal decorrelation and relatively small heights of ambiguity.

Since long it is known that SAR interferometric observables are influenced by soil moisture variations, however there is a lack of scattering models that link interferometric observables and variations of the dielectric properties. In this work we propose a model based on plane waves and Born approximation, deriving first the vertical wavenumbers in the medium as a function of geometrical and dielectric properties and successively the interferometric coherences. It is observed that soil moisture behaves on the phase in a similar way as tomography does, breaking the phase consistency in triplets of interferograms. This property, along with coherence magnitudes, is exploited in an attempt at moisture inversion on real data.

This paper discusses cross-track SAR interferometry under crossing orbits. The underlaying theory is briefly outlined, showing that a crossing angle between the ground tracks needs to be compensated by applying different squint angles in order to have overlap in the the ground-spectral domain. Two sets of crossing orbits InSAR experiments are described. The results of the first experiment, are discussed.

This paper discusses the implementation of an end- to-end simulator for the BIOMASS mission. An overview of the system architecture is provided along with a functional description of the modules that comprise the simulator.

Tandem-L is a mission proposal for an innovative interferometric L-band radar instrument that enables the systematic monitoring of dynamic Earth processes using advanced techniques and technologies. The mission is science driven aiming to provide a unique data set for climate and environmental research, geodynamics, hydrology and oceanography. Important application examples are global forest height and biomass inventories, measurements of Earth deformation due to tectonic processes and/or anthropogenic factors, observations of ice/glacier velocity field and 3-D structure changes, and the monitoring of soil moisture and ocean surface currents. The Tandem-L mission concept consists of two cooperating satellites flying in close formation. The Pol-InSAR and repeat-pass acquisition modes provide a unique data source to observe, analyse and quantify a wide range of mutually interacting processes in the bio-, litho-, hydroand cryosphere. The systematic observation of these processes benefits from the high data acquisition capacity and the novel high-resolution wide-swath SAR imaging modes that combine digital beamforming with a large reflector antenna. This paper provides an overview of the Tandem-L mission concept and its main application areas. It is planned to realise the Tandem-L mission in cooperation with NASA/JPL. The mission concept was developed in detail in a joint two-year pre-phase A study and it will be further studied in the next 18 months. This will allow a cost-effective implementation, whereby each partner contributes its predevelopments and experience. According to current planning, the Tandem-L satellites could be launched in 2019.

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.

In summer 2010 during the commissioning phase of TanDEM-X, the TerraSAR-X/TanDEM-X constellation was operated in the pursuit monostatic mode allowing along-track interferometric measurements with very short time separation of only 2.6 sec. This paper presents first evaluations of data acquired on arctic sea ice scenarios and investigates the potentials for the mapping of ice sheet dynamics with respect to rotation and translation with this unique constellation. Due to the larger coverage, the data analysis is focused on interferometric ScanSAR data.

Large datasets of satellite SAR missions dedicated to deformation monitoring will require intensive and dedicated interferometric processing techniques. Decorrelation effects will prevent simple processing approaches, but optimal algorithms are computationally intensive. This paper shows results of a novel efficient algorithm that aims at exploiting scatter component that are stable over time, without being isolated point targets. The concept is proved valid for simulated data and limited examples in X-band and L-band.

This letter describes the first interferometric acquisitions and results obtained by the TerraSAR-X add-on for Digital Elevation Measurements mission. Due to the large along-track separation between the two satellites during the approaching maneuver and the Earth's rotation, useful interferometric acquisitions were only possible at high latitudes. This resulted in a crossing angle between the ground tracks whose impact was corrected by acquiring the two synthetic-aperture radar images with an opposite squint. The still very large 2-km cross-track baseline resulted in a 3.8-m interferometric height of ambiguity, producing extremely detailed images of the topography of the target area. Results acquired over the October Revolution Island, Russia, are shown and discussed.

Speckle tracking is used with synthetic aperture radar (SAR) images to estimate displacements, in ways that support or integrate interferometric measurements. This letter derives Fisher information expressions for the displacement estimation using coherent speckle tracking, for the multi-image scenario with an arbitrary coherence structure. Previous results were limited to image pairs. An estimator that approaches the theoretical bound is also proposed, establishing a link with phase estimation for multi-image SAR interferometry. The derivation of the Fisher information is given in the general case when the coherence is a function of the frequency.

This letter shows that in a repeat-pass data set of synthetic aperture radar (SAR) images, a long-term coherent component, when present, can be recovered by coherent temporal filtering of the SAR images and can successively form interferograms with higher signal-to-noise ratio. The validity of the idea is confirmed through simulations and one example with real TerraSAR-X data. The theoretical necessity of using long-term interferograms is also discussed and linked to autoregressive processes, starting from the observation that the optimal weighting is given by the inverse of the covariance matrix.

SIGNAL is an innovative earth exploration mission proposal with the main objective to estimate accurately and repeatedly topography and topographic changes associated with mass change or other dynamic effects on glaciers, ice caps and polar ice sheets. Elevation measurements are complemented with glacier velocity measurements, providing valuable additional information for a better understanding of the hydrology of glacierized basins and of the Arctic and Antarctic water cycle. SIGNAL is capable of monitoring all critical regions with a high spatial resolution and an adequate revisit time. This paper gives an overview about the actual mission design status and provides a brief description of the topography (DEM - digital elevation map) self-calibration strategy and the estimated global interferometric performance.

Tandem-L is a proposal for an innovative interferometric and polarimetric radar mission that enables the systematic monitoring of dynamic processes on the Earth surface. Important mission objectives are global forest height and biomass inventories, large scale measurements of millimetric displacements due to tectonic shifts, and systematic observations of glacier movements. The innovative mission concept and the high data acquisition capacity of Tandem-L provide a unique data source to observe, analyze and quantify the dynamics of a wide range of mutually interacting processes in the bio-, litho-, hydro- and cryosphere. By this, Tandem-L will be an essential step to advance our understanding of the Earth system and its intricate dynamics.

Tandem-L is an L-band SAR satellite mission currently under study at DLR. It is intended to serve a number of geophysical applications in several domains, like solid Earth, ecosystems and cryosphere. The various applications compete for the system resources and the mission design optimization requires that a performance model is developed for each application in order to allow motivated choices. We describe the adopted approach for deformation measurements, which is based on recent formulations of the Cramer-Rao bound for multi-image SAR interferometry and on the a-posteriori combination of the measurements from different lines of sight. We also discuss the limitations that the use of a reduced set of interferograms would entail.

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

In the past years, PS analysis has shown its ca- pability to treat simultaneously long series of SAR data. In this contribution an attempt is made to overcome some of the limitations of the said technique, namely its negligence of decorrelation phenomena; a maximum likelihood estimator for the physical parameters of interest is described and some results are presented. I. INTRODUCTION During the past decade the availability of long series of coherent SAR images led to the development of multiple- image processing techniques. The advantages of such joint analyses over convetional DInSAR are an increased capability in distinguishing the various contributions to the interferomet- ric phase and consequently a better estimate of atmospheric delay variations, one of the most severe limitations to accurate ground deformation recovery. We refer in particular to the PS technique (1), which has proven very effective in identifying stable scatterers, with respect to their phase properties, expecially over urbanized areas. The PS technique, in its stricter version, requires the target to possess some well defined geometrical and temporal characteristics: its cross-range extension must be limited and its reflectivity should not change over the entire data set time span. When these requirements are not met by the radar target, the estimates of physical parameters on it are considered unreliable and the point discarded. Different ways to overcome this limitation have already been proposed. With respect to temporal decorrelation we recall for instance the Semi-PS/Temporary-PS concept (2), tackling the case in which a target appears or disappears at some point in the amplitude time series (e.g. when a new building is contructed). Moreover, it is common practice to discard images because of their time isolation or because they represent areas temporary covered by snow (such as winter images in the Alps), since they have no or little chance to be coherent with the main bunch of the data set. With respect to geometric decorrelation we recall the SBAS technique which carries out the analysis only on small baseline subsets (3) and the so called higher order interferometry (4) which models the presence of two dominant scatterers in the resolution cell (with different cross-range positions). In this paper we present a new attempt of overcoming the above mentioned limitations of standard PS interferometry. The goal is to complete successful estimations of the param- eters of interest on a larger number of points. In Section II the expression of a Maximum Likelihood estimator is derived from a statistical characterization of SAR observables and real data results are presented. Eventually, some considerations are made on the underlying mechanisms of the proposed estimator and on its proximity to standard PS analysis.