Progressive Scans Research Articles

A priori parameter estimation of space SAR operating in the sliding spotlight scan mode and in the terrain observation mode by progressive scans

In the detailed mode of operation of the synthetic aperture radar (SAR), an improved level of geometric resolution of the terrain in a small frame is achieved. If, however, the frame length exceeds the size of the bottom trace in the azimuthal direction, then it is necessary to use a sliding spotlight operation mode (SSL), in which antenna pattern is scanned in the swath along the azimuth angle. To increase the width of the swath, ScanSAR mode is used. In the traditional implementation of this mode, image serration occurs. This effect can be eliminated by using terrain observation by progressive scans mode (TOPS)). In this mode, when shooting a frame, the antenna pattern runs quickly and alternately through all the specified partial swath bands. Despite the presence of a large number of publications in domestic and foreign literature devoted to the analysis of the main parameters of SAR operating in SSL and TOPS modes, there is a need to clarify calculation methods and increase the number of system parameters issued by them, which generally determine the basic appearance of the equipment. The purpose of the work is to clarify and detail the presentation of the methodology for a priori estimation of an increased number of parameters describing the main system characteristics of space SAR operating in SSL and TOPS. The paper develops and describes in detail a methodology with an exhaustive list of calculation ratios for a priori estimation of parameters describing the main system characteristics of space SAR operating in SSL and TOPS. Based on it, algorithms and software modules have been developed that allow you to perform calculations and display the results in a visual graphical form. Examples of computer calculations of 12 system parameters dependencies on the angle of sight of space radars operating in these two modes are given. The application of the developed methodology makes it possible to quickly perform an a priori assessment of a variety of basic system parameters of space radars operating in SSL and TOPS modes, which facilitates the selection of the most acceptable basic appearance of the equipment for practical implementation.

Giving information strategically and transparently: A pilot trial of the Oncolo-GIST intervention to promote patients' prognostic understanding.

Most patients with cancer lack the prognostic understanding necessary to make informed decisions. We tested the feasibility and acceptability of the Oncolo-GIST ("Giving Information Strategically and Transparently, GIST") intervention and explored its associations with patients' improved prognostic understanding. The Oncolo-GIST intervention distills prognostic discussions into easy-to-understand talking points. Patients with metastatic cancers that progressed on ≥1 line of chemotherapy and not expected to survive 12 months (n = 31) were recruited from October 2020 through November 2022. We compared patients who discussed their progressive scans with an oncologist trained in the GIST technique or not (i.e., usual care). A primary outcome was prognostic understanding (e.g., patients reporting a life-expectancy of months) assessed within a week of the scan discussion visit. Oncologists (n = 4) appeared receptive to the Oncolo-GIST intervention and scored nearly perfectly on post-training tests of material mastery after a < 2-h tutorial. Post-scan discussion visit, 100% of patients who met with an Oncolo-GIST-trained clinician understood that their cancer was considered incurable (a 31% improvement from pre-visit) compared with 91% of patients meeting with usual care oncologists (an 18% improvement); 33% of patients who met with an Oncolo-GIST-trained oncologist understood that they likely had months, not years, compared to 18% in the usual care group. No statistically significant differences emerged for these changes, nor for therapeutic alliance, anxiety, or depression scores between groups. Oncolo-GIST appears to be an easily learned approach to improve prognostic understanding that neither undermines therapeutic alliances nor increases patients' anxiety or depressive symptoms. Efficacy testing in a larger trial is warranted.

Fault Geometry, Slip Distribution, and Potential Triggering of the 2022 Mw 6.2 Deadly Afghanistan Earthquake Revealed from Geodetic and Weather Data

Abstract The 22 June 2022 Mw 6.2 Khōst, Afghanistan, earthquake struck killing more than 1700 people and devastating the region. For studying this earthquake, we computed the coseismic deformation fields of the earthquake using the Sentinel-1 Terrain Observation with Progressive Scans Interferometric Synthetic Aperture Radar (InSAR). The InSAR results show that the maximum coseismic displacement in the satellite line of sight direction reaches up to 39 cm. We determined the geometric parameters of the fault and coseismic slip distribution from these InSAR measurements. The best-fitted fault model shows that the rupture occurred on a right-lateral strike-slip fault with a strike of 203.7° and a dip of 68°. The most slip is concentrated at a shallow depth within the upper 10 km with the maximum slip of ∼3 m at 2.5 km depth. The maximum slip produced by this earthquake is significantly larger than the slip produced by several other similar earthquakes with similar magnitudes, implying that the focused shallow slip is likely the reason for the significant damage in the earthquake. The heavy rainfall was recorded during the earthquake period, which resulted in complicated fringes in coseismic interferograms close to the earthquake in time. Because a positive spatial and temporal correlation with the earthquake occurrence can be seen, the rainfall may have potential contributions to the earthquake, which deserves additional analysis in future. Combined with the potential effects of the 2015 Mw 7.5 Hindu Kush deep-seated earthquake, the seismicity in Afghanistan is the result of the ongoing subduction of the Indian plate beneath the Eurasian plate along their west boundary.

An enhanced spectral diversity coregistration method for dual-polarimetric Sentinel-1A/B TOPS data

Sentinel-1A/B data are crucial for retrieving numerical information about surface phenomena and processes. Coregistration of terrain observation by progressive scans (TOPS) data is a critical step in its application. TOPS data must be fundamentally co-registered with an accuracy of 0.001 pixels. However, various decorrelation factors due to natural vegetation and seasonal effects affect the coregistration accuracy of TOPS data. This paper proposed an enhanced spectral diversity coregistration method for dual-polarimetric (PolESD) Sentinel-1A/B TOPS data. The PolESD method suppresses speckle noise based on a unified non-local framework in dual-pol Synthetic Aperture Radar (SAR), and extracts the phase of the optimal polarization channel from the denoised polarimetric interferometric coherency matrix. Compared with the traditional ESD method developed for single-polarization data, the PolESD method can obtain more accurate coherence and phase and get more pixels for azimuth-offset estimation. In bare areas covered with low vegetation, the number of pixels selected by PolESD is more than the Boxcar method. It can also correct misregistration more effectively and eliminate phase jumps in the burst edge. Therefore, PolESD will help improve the application of TOPS data in low-coherence scenarios.

Monitoring of Water and Tillage Soil Erosion in Agricultural Basins, a Comparison of Measurements Acquired by Differential Interferometric Analysis of Sentinel TopSAR Images and a Terrestrial LIDAR System

Agricultural production, the main pillar of food security, is highly dependent on soil quality, and threatened by erosion processes that degrade soil quality. This article is part of a research to verify the usefulness of differential interferometric analysis on TopSAR (Terrain Observation with Progressive Scans SAR, Synthetic Aperture Radar) images to measure water and tillage erosion in small agricultural basins. For this, images from the Sentinel 1 mission are used, analyzing the deformations on the earth’s surface. The purpose of this research is to verify the accuracy of the proposed method by comparing its measures with the ones taken with the gold standard laser terrestrial LIDAR (Light Detection and Ranging) system, as well as to establish a basic step period framework that guarantees an admissible loss of coherence. The results on a pilot plot in El Molar (north of Madrid, Spain) showed that the differences lay within the range of the error associated with the very LIDAR system and showed that coherence losses correspond with the deformations measured. Given the economic and labor advantages of the differential interferometric analysis, this method could be regarded as an excellent alternative to the use of LIDAR in large-scale studies for measuring ground deformation caused by water and tillage erosion.

A Joint Parameters Estimation Method for Azimuth Multichannel TOPS SAR

Multi-channel parameter estimation is a key technology for azimuth multi-channel terrain observation by progressive scans synthetic aperture radar (MC TOPS SAR) systems. Normally, for the traditional multichannel parameter estimation algorithms, the mismatch parameters are concluded as phase error, baseline error, and Doppler centroid. The beam rotation speed error is ignored. However, for MC TOPS SAR, beam rotation speed error will degrade the reconstruction performance of the Doppler spectrum. Moreover, only part of the mismatch parameters can be estimated for the traditional algorithms. To address those problems, a joint parameters estimation algorithm for TOPS SAR based on spatial time cross-correlation coefficient (STCCC) is proposed. Combined with phase wrapping and the least-squares method (LSM), the algorithm is capable of realizing a joint parameters estimation of channel consistency error, azimuth baseline error, Doppler centroid frequency, and beam rotation speed estimation without iteration. The real data processing result shows that the method can effectively realize MC TOPS SAR data error estimation.

The influence of Sentinel-1 SAR sub-swath on the recorded backscatter time-series over managed hemiboreal forests

Abstract The view angle range of Sentinel-1 SAR in the Interferometric Wide swath (IW) measurement mode is 29.1° – 46.0°. The dependence of backscatter on the arbitrary local incidence angle is usually corrected using a linear regression model where the incidence angle is a predictor variable. We analysed the whole time series of Sentinel-1 SAR VV-polarised backscatter over the flat 15×15 km test site in Laeva, Estonia (26° 26′ 43″ E; 58° 31′ 56″ N). Time series containing measurements from three different orbits were constructed for 3,159 stands from nighttime data and for 1,105 stands from daytime data. We can confirm that daytime backscatter is systematically greater than nighttime backscatter. We found a significant deviation from linearity in the backscatter dependence on local incidence angle. The empirical finding may be caused by the microwave scattering dependence on local incidence angle or by the influence of Sentinel-1 SAR sub-swath configuration in the Terrain Observation with Progressive Scans SAR (TOPSAR) method that is used for the measurements.

An MT-InSAR Data Partition Strategy for Sentinel-1A/B TOPS Data

The Sentinel-1A/B satellite launched by European Space Agency (ESA) in 2014 provides a huge amount of free Terrain Observation by Progressive Scans (TOPS) data with global coverage to the public. The TOPS data have a frame width of 250 km and have been widely used in surface deformation monitoring. However, traditional Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) methods require large computer memory and time when processing full resolution data with large width and long strips. In addition, they hardly correct atmospheric delays and orbital errors accurately over a large area. In order to solve these problems, this study proposes a data partition strategy based on MT-InSAR methods. We first process the partitioned images over a large area by traditional MT-InSAR method, then stitch the deformation results into a complete deformation result by correcting the offsets of adjacent partitioned images. This strategy is validated in a flat urban area (Changzhou City in Jiangsu province, China), and a mountainous region (Qijiang in Chongqing City, China). Compared with traditional MT-InSAR methods, the precision of the results obtained by the new strategy is improved by about 5% for Changzhou city and about 15% for Qijiang because of its advantage in atmospheric delay correction. Furthermore, the proposed strategy needs much less memory and time than traditional methods. The total time needed by the traditional method is about 20 h, and by the proposed method, is about 8.7 h, when the number of parallel processing is 5 in the Changzhou city case. The time will be further reduced when the number of parallel processes increases.

Fast InSAR Time-Series Analysis Method in a Full-Resolution SAR Coordinate System: A Case Study of the Yellow River Delta

Ground deformation is a major determinant of delta sustainability. Sentinel-1 Terrain Observation by Progressive Scans (TOPS) data are widely used in interferometric synthetic aperture radar (InSAR) applications to monitor ground subsidence. Due to the unparalleled mapping coverage and considerable data volume requirements, high-performance computing resources including graphics processing units (GPUs) are employed in state-of-the-art methodologies. This paper presents a fast InSAR time-series processing approach targeting Sentinel-1 TOPS images to process massive data with higher efficiency and resolution. We employed a GPU-assisted InSAR processing method to accelerate data processing. Statistically homogeneous pixel selection (SHPS) filtering was used to reduce noise and detect features in scenes with minimal image resolution loss. Compared to the commonly used InSAR processing software, the proposed method significantly improved the Sentinel-1 TOPS data processing efficiency. The feasibility of the method was investigated by mapping the surface deformation over the Yellow River Delta using SAR datasets acquired between January 2021 and February 2022. The findings indicate that several events of significant subsidence have occurred in the study area. Combined with the geological environment, underground brine and hydrocarbon extraction as well as sediment consolidation and compaction contribute to land subsidence in the Yellow River Delta.

An Efficient Global Scale Sentinel-1 Radar Backscatter and Interferometric Processing System

We describe an efficient and cost-effective data access mechanism for Sentinel-1 Terrain Observation with Progressive Scans (TOPS) mode bursts. Our data access mechanism enables burst-based data access and processing, thereby eliminating the European Space Agency’s (ESA’s) Sentinel-1 Single Look Complex (SLC) data packaging conventions as a bottleneck to large scale processing. The pipeline throughput is now determined by the available computation resources and the efficiency of the analysis algorithms. For targeted infrastructure monitoring studies, we are able to generate coregistered, geocoded stacks of SLCs for any area of interest (AOI) in the world, in a few minutes. In addition, we describe our global scale radar backscatter and interferometric products, and associated pipeline design decisions that ensure geolocation consistency across the suite of derived products from Sentinel-1 data. Finally, we discuss the benefits and limitations of working with geocoded SLC data.

Monitoring Potential Geological Hazards with Different InSAR Algorithms: The Case of Western Sichuan

In recent years, the number of geological disasters in Sichuan Province has significantly increased due to the influence of earthquakes and extreme climate, as well as the disturbance to the geological environment by human activities. Thus, geological disaster monitoring is particularly important, which can provide some scientific basis for disaster prevention and reduction. In this paper, the interferometric synthetic aperture radar (InSAR) technology was introduced to monitor potential geological hazards, taking parts of Dujiangyan City, Wenchuan County, and Mao County in Sichuan Province, China as examples. Firstly, the data such as Sentinel-1A Terrain Observation with Progressive Scans (TOPS) Synthetic Aperture Radar (SAR) images and Precision Orbit Determination (POD) precise orbit ephemerides from 2018 to 2020, high-resolution optical satellite images and Digital Elevation Model (DEM) were collected. Secondly, the Differential InSAR (D-InSAR), Persistent Scatterer InSAR (PS-InSAR), Small Baseline Subset InSAR (SBAS-InSAR), Offset-Tracking, and Distributed Scatterer InSAR (DS-InSAR) algorithms were used to invert the surface deformation of the study area. Thirdly, according to the deformation results obtained by experiments, we used GF-1 and GF-2 optical images as a reference and combine the experimental results of InSAR algorithms to delineate the areas affected by geological disasters. A total of 49 geological disaster areas were obtained, mainly including landslides, collapses, and debris flow. Through field verification, the overall accuracy rate of InSAR deformation monitoring achieved 69.23%, and the accuracy rate of new potential hazards monitoring reached 63.64%. Among all InSAR methods, the DS-InSAR method outperformed and monitored the geological disaster areas well. Finally, the study area was divided into three elevation intervals and the applicability of different InSAR algorithms in different elevation intervals was discussed.

Study on Airborne Near-Nadir TOPS SAR Imaging With Attitude Angle Error

Combined with terrain observation by progressive scans (TOPS) synthetic aperture radar (SAR), near-nadir SAR (N-SAR) system has great potential for the surface water and ocean topography (SWOT) observation. However, one practical problem of the airborne N-SAR is the non-ideal attitude angle caused by the environment. Normally, the influence of attitude angle error can be considered as a constant squint angle of the system. However, in fact, for the near-nadir SAR system with TOPS SAR mode, the attitude angle error will cause a non-ideal 2-dimensional space-variant Doppler centroid for the receiving data and cause the traditional imaging algorithm failure. To deal with such problems, an imaging algorithm with attitude angle estimation for the near-nadir TOPS SAR system is proposed in this paper. Firstly, the influence of attitude angle error and the signal properties are analyzed. Secondly, based on the analysis, an attitude angle estimate algorithm (AAE), utilizing the nonlinear least square method (NLSM) and minimum entropy criterion, is proposed. Then, based on the estimated altitude angle, without data blocking, a full data imaging algorithm (FDA) is proposed. Its main idea is to obtain an un-ambiguous azimuth spectrum and design an appropriate range-variant azimuth filter through frequency chirp scaling (FCS). The numerical simulations and real data processing demonstrate that the proposed algorithm has good performance on attitude angle error estimation and well-focused image obtaining.

Design and Performance Analysis of Sparse TOPS SAR Mode

Terrain observation by progressive scans (TOPS) is a novel and promising wide-swath synthetic aperture radar (SAR) imaging mode, which overcomes the scalloping effect existing in ScanSAR. Traditional imaging algorithms are computationally efficient in raw data processing of TOPS, but the problems from clutter and sidelobes suppression have not been effectively solved. Sparse SAR imaging not only effectively solves these problems, but also has great potential in improving system performance, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e.g.</i> , lower requirement of pulse repetition frequency (PRF), higher swath coverage, less data amount, and lower system complexity. Therefore, this paper proposes a novel sparse TOPS SAR imaging mode. The proposed mode combines advantages of sparse imaging system and TOPS mode to achieve high-quality and wide-swath SAR imaging. In this mode, we first design the beam position by timing diagram. Then the basic parameters of the mode are calculated according to the radar equation, and the properties such as grating lobes are analyzed. Finally, an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$L_{2,1}$</tex-math></inline-formula> -norm regularization based sparse TOPS SAR imaging algorithm is introduced to achieve the high-quality sparse scene recovery. Experimental results show that compared with conventional TOPS imaging mode, the proposed mode can obtain wide swath with lower PRF and effectively solve the effect on distributed target ambiguity ratio (DTAR). Compared with matched filtering (MF) based TOPS imaging algorithm, the sparse method can achieve unambiguous reconstruction of the considered scene from down-sampled data, and obtain the image with less artifacts.

A Compressive-Sensing Approach for Opportunistic Bistatic SAR Imaging Enhancement by Harnessing Sparse Multiaperture Data

This article introduces a compressive sensing (CS)-based approach for increasing bistatic synthetic aperture radar (SAR) imaging quality in the context of a multiaperture acquisition. The analyzed data were recorded over an opportunistic bistatic setup including a stationary ground-based-receiver opportunistic C-band bistatic SAR differential interferometry (COBIS) and Sentinel-1 C-band transmitter. Since the terrain observation by progressive scans (TOPS) mode is operated, the receiver can record synchronization pulses and echoed signals from the scene during many apertures. Hence, it is possible to improve the azimuth resolution by exploiting the multiaperture data. The recorded data are not contiguous and a naive integration of the chopped azimuth phase history would generate undesired grating lobes. The proposed processing scheme exploits the natural sparsity characterizing the illuminated scene. For azimuth profiles recovery greedy, convex, and nonconvex CS solvers are analyzed. The sparsifying basis/dictionary is constructed using the synthetically generated azimuth chirp derived considering Sentinel-1 orbital parameters and COBIS position. The chirped-based CS performance is further put in contrast with a Fourier-based CS method and an autoregressive model for signal reconstruction in terms of scene extent limitations and phase restoration efficiency. Furthermore, the analysis of different receiver-looking scenarios conducted to the insertion in the processing chain of a direct and an inverse Keystone transform for range cell migration (RCM) correction to cope with squinted geometries. We provide an extensive set of simulated and real-world results that prove the proposed workflow is efficient both in improving the azimuth resolution and in mitigating the sidelobes.

A Real-Time Unified Focusing Algorithm (RT-UFA) for Multi-Mode SAR via Azimuth Sub-Aperture Complex-Valued Image Combining and Scaling

Spaceborne synthetic aperture radar (SAR) can operate at various modes, including stripmap mode, spotlight mode, sliding spotlight mode, and Terrain observation by progressive scans (TOPS) mode. These four imaging modes can be regarded as unified, differing in rotation-center ranges. To uniformly focus the data of these four imaging modes in real-time, this article proposes a real-time unified focusing algorithm (RT-UFA) for the multi-mode SAR via azimuth sub-aperture complex-valued image combining and scaling. The imaging processing can be performed while the data are being recorded. In the first stage of imaging, sub-aperture complex-valued images with relative low-resolution can be obtained by the cascade of the extended chirp scaling (ECS) and azimuth dechirp. Then, these complex-valued images are coherently combined by shifting the integer number of pixels, and thus the full-resolution image of all the recorded data can be obtained. The azimuth scaling and the pixels shifting in the RT-UFA are analyzed in detail. Simulation and SAR data results are presented to validate the analysis and RT-UFA.

Improving the Split-Spectrum Method for Sentinel-1 Differential TOPSAR Interferometry

Differential SAR interferometry (DInSAR) is a useful technique used to measure small movements and surface deformation. However, ionospheric phase screens are a major error source in multipass terrain observation by progressive scans sar (TOPSAR) interferograms. In this letter, an improved split-spectrum method is proposed. First, the burst used for ionospheric phase estimation is selected through coherence, and then, the ionospheric phase of the burst is estimated based on the split-spectrum method. Finally, the TOPSAR ionospheric space-variable phase in a large scene is obtained through 2-D space-variable fitting, which avoids the complicated processing of splicing between bursts of different periods and reduces the number of unwrapping calculations for large scenes after splicing. The method can ensure that the number of calculations is reduced without loss of accuracy. Sentinel-1 TOPSAR real data processing verifies the correctness of the proposed method.

An Integrated Approach for Mapping Three-Dimensional CoSeismic Displacement Fields from Sentinel-1 TOPS Data Based on DInSAR, POT, MAI and BOI Techniques: Application to the 2021 Mw 7.4 Maduo Earthquake

Sentinel-1 Terrain Observation by Progressive Scans (TOPS) data have been widely applied in earthquake studies due to their open-source policy, short revisit cycle and wide coverage. However, significant near-fault displacement gradients and the moderate azimuth resolution of TOPS data make achieving high-precision along-track measurements challenging, which prevents the generation of high-quality three-dimensional (3D) displacement maps. Here, we propose an integrated method to retrieve high-quality 3D displacements based on the differential interferometric SAR (DInSAR), burst-overlap interferometry (BOI), multiple-aperture InSAR (MAI) and pixel offset tracking (POT) techniques, which are achieved to use only two track Sentinel-1 TOPS data with different viewing geometries. The key step of this method is using a weighted fusion algorithm with the interpolated BOI-derived and MAI-derived 3D displacements. In a case study of the 2021 Maduo earthquake, the calculated root mean square errors (RMSEs) from global navigation satellite system (GNSS) data and the InSAR-derived 3D displacement fields were found to be 6.3, 5.8 and 1.7 cm in north–south, east–west and up–down components, respectively. Moreover, the slip model of the 2021 Maduo earthquake jointly estimated by DInSAR and BOI measurements indicates that this seismic event was dominated by sinistral strike-slip motion mixed with some dip-slip movements; the estimated seismic moment was 1.75 × 1020 Nm, corresponding to a Mw 7.44 event.

Differential Interferometry over Sentinel-1 TopSAR Images as a Tool for Water and Tillage Soil Erosion Analysis

Erosion is a major problem on agricultural lands in Europe. Erosion measurement tools have traditionally been focused on delocalized quantification but without mapping the real places inside the basin where the erosion took effect. In this article, we use new space missions, such as Sentinel-1, and the opportunity they offer to obtain SAR (Synthetic Aperture Radar) images with high frequency, resolution, range, and, above all, availability to enable the application of techniques, like differential interferometry, in new fields. We propose to measure ground deformation caused by water and tillage erosion in small agricultural basins using TopSAR (Terrain Observation with Progressive Scans SAR, Synthetic Aperture Radar) images acquired by the Sentinel-1 mission, after previously verifying the accuracy of these measurements through comparison with measurements from a LIDAR (Light Detection and Ranging) system. The results of this work confirm the potential of monitoring erosion in agricultural basins with differential interferometry over Sentinel-1 TopSAR images. Its capabilities have been successfully tested in different conditions related to agricultural tasks without precipitation or storm events. This technique makes it possible to study both water and tillage erosion and sedimentation processes and even to test the efficiency of anti-erosion measures in the field or to verify the results of different management practices over time.

Toward a Comprehensive Dam Monitoring: On-Site and Remote-Retrieved Forcing Factors and Resulting Displacements (GNSS and PS–InSAR)

Many factors can influence the displacements of a dam, including water level variability and environmental temperatures, in addition to the dam composition. In this work, optical-based classification, thermal diachronic analysis, and a quasi-PS (Persistent Scatter) Interferometric SAR technique have been applied to determine both forcing factors and resulting displacements of the crest of the Castello dam (South Italy) over a one-year time period. The dataset includes Sentinel-1A images acquired in Interferometric Wide swath mode using the Terrain Observation with Progressive Scans SAR (TOPSAR); Landsat 8 Thermal Infrared Sensor (TIRS) thermal images, and Global Navigation Satellite System (GNSS) for interpreting the motion of the top of the dam retrieved via interferometry. Results suggest that it is possible to monitor both dam water level and temperature periodic forcing factors and resulting displacements via a synergistic use of different satellite images.

Burst Overlap Coregistration for Sentinel-1 TOPS DInSAR Ice Velocity Measurements

The application of Sentinel-1 interferometry to ice velocity measurements has until recently been limited by the significant horizontal scene motion associated with ice flow, which causes phase discontinuities (and associated unwrapping problems) at burst boundaries in Terrain Observation by Progressive Scans (TOPS) interferograms. Coregistering with a multiyear averaged external velocity mosaic based on offset-tracking can account for the bulk of the ice motion, but residual discontinuities sometimes remain, for example, due to seasonal variations in the ice velocity, or due to error sources such as azimuth shifts caused by ionospheric propagation. The presented method extends the external velocity coregistration with a local, spatially varying, coregistration in the burst overlap regions. This is based on the extended spectral diversity principle, which can only be applied in the overlap regions, but offers superior accuracy and resolution compared with traditional coregistration methods. The method considerably reduces phase discontinuities at burst boundaries, and potential new phase discontinuities at the overlap region edges are suppressed by an azimuth tapering of the applied coregistration shifts. An example scene is presented, and the phase discontinuities before and after application of the method are evaluated. The method is seen to remove phase discontinuities, with no adverse effects.