Synthetic Aperture Radar Processing Research Articles

A Stretched Deramping Radar Technique for High-Resolution SAR Processing in Ka-Band Using the Extended Integration Time

To increase the image quality of Synthetic Aperture Radar (SAR) is one of the hot-issue for high-performance detection/reconnaissance. With this interest in the SAR technique, it generates various techniques according to the purposed platforms (Auto-SAR, ViSAR, InSAR, PolSAR, etc.). In this paper, we introduce high efficiency and useful techniques, which can be applied to various SAR applications for generating high-quality images in Ka-band. We propose stretched de-ramping hardware system applicable in Ka-band, and design the Range-Doppler algorithm which well matches the proposed radar system with the modified signal parameters. Thus, we can extend the integration time of the convolution process in slow-time and it leads to the improvement of the SAR image quality. To verify the performance of our proposed technique, we process the practical experiments at conventional outdoor fields. Furthermore, the proposed method is operated on Range Doppler Algorithm (RDA), which is mostly used for standard SAR.

Potential of Two SAR-Based Flood Mapping Approaches in Supporting an Integrated 1D/2D HEC-RAS Model

This study investigates the potential of Sentinel-1 data in assisting flood modeling procedures. Two different synthetic aperture radar (SAR) processing methodologies, one simplified based on single-flood image thresholding and one automatic based on SAR statistical temporal analysis, were exploited to delineate the flooding caused by a storm event that took place in Spercheios River, Central Greece. The storm event was simulated by coupling a HEC-HMS hydrologic model and an integrated 1D/2D HEC-RAS hydraulic model. Both SAR methodologies were compared to each other and also used as a reference to test the sensitivity of the hydraulic model in the variation of upstream discharge and roughness coefficient. Model sensitivity was investigated with respect to the change in the derived inundation extent and three additional metrics: the Critical Success Index (CSI), the Hit Rate (HR), and the False Alarm Ratio (FAR). The model response was found to be affected in the following order: by the upstream inflow, and by the variation of the roughness coefficient in the main channel and in the land use “cultivated crops”. The discrepancies observed between model- and SAR-derived inundation products are associated with the uncertainty accompanying the SAR processing and the utilized satellite data itself, the underlying topography, and the structural uncertainty inherent in the modeling procedure. Regarding the SAR methodologies tested, the second one (FLOMPY approach) proved to be more suitable, yielding a more coherent and realistic flooded area. According to the applied metrics and considering as reference the FLOMPY result, model performance ranged between 22–27.5% (CSI), 36.9–60.4% (HR), and 62.1–68.2% (FAR).

Earthquake-induced risk assessment of cultural heritage based on InSAR and seismic intensity: A case study of Zhalang temple affected by the 2021 Mw 7.4 Maduo (China) earthquake

Earthquakes have been acknowledged as threats to heritages for a long time in the past decades. Many scientific publications and international guidelines have addressed this issue. However, the related reports are still lacking particularly for the 2021 Mw 7.4 Maduo earthquake and its surrounding heritage sites, even though this event was the largest earthquake in China after 2008 with 13 National Key Protected Cultural Relic Units (NKPCRUs) of China located in the surrounding areas within 200 km from the epicenter. On May 21, 2021, an Mw 7.4 earthquake struck Maduo County in Qinghai Province, China. The earthquake was large in magnitude and caused ∼150 km of surface rupture. The integrity and authenticity of cultural heritages near the epicenter are under severe threat, making it critically important to quantify the potential damages and vulnerability of these sites affected by the Mw 7.4 earthquake. Nevertheless, many geological and geophysical studies related to this earthquake have been conducted, but none of them consider the seismic damage to the heritage sites. To fulfill this gap, the Zhalang temple (also known as “Golok Peaceful Liberation Memorial”) which was a Tibetan Buddhist monastery located ∼140 km away from the Mw 7.4 epicenter of the 2021 Maduo earthquake was taken as an example to investigate whether and how the strong earthquake could affect a cultural heritage in such a distance. Collaborative monitoring based on InSAR and seismic intensity was conducted to measure the earthquake-induced deformation and characterize the risks and damages to cultural heritages by earthquakes. First, fast responses within 30 min based on the seismic method were performed. The PGV-vS30 intensity, that was the peak ground velocities (PGV) further site-corrected by the site conditions of the time-averaged shear-wave velocity to 30 m depth (vS30) seismic intensity map was obtained, which provided a general and fast guidance to preliminary determinations of the severe disaster area and the scope of the disaster area. Initial decisions could be made about whether or where a certain location should be taken into further on-site inspection. Then, the Interferometric Synthetic Aperture Radar (InSAR) processing of Sentinel-1 images was performed to define two-dimensional (2D) East-West (E-W) and vertical co-seismic deformation maps near the Zhalang temple. Finally, the measurements obtained by seismic and InSAR methods were validated by unmanned aerial vehicle (UAV) imagery and field surveying. The results showed that: the maximum E-W striking deformation was ∼2.54 cm toward the east and the vertical subsidence was ∼0.01 cm centered on the Zhalang temple, suggesting that the E-W striking deformation significantly affected the surrounding region. Moreover, the spatial heterogeneity indicator of the InSAR deformation maps revealed the locations of underground faults with surface expressions. Further field survey detected surface fractures at Zhalang temple due to secondary effects of the Mw 7.4 earthquake. The genetic process of faulting and fracturing is crucial in terms of hazard assessment and mitigation strategies. In countries with strong environmental and seismic risks, the presented work contributes to the disaster risk reduction (DRR) of heritages in natural-hazard-prone areas and also takes on a social value because it provided supplements for the protection of a heritage that represents the very identity nationwide.

Study on processing synthetic aperture radar data based on an optical 4f system for fast imaging.

Due to the huge amount of collected echo data caused by the working principle of synthetic aperture radar (SAR), the use of digital processing relies heavily on the performance of digital chips. Because of the limitation of Moore's law, the technology of digital signal processing exposes the limitation of computing speed and power consumption in the face of SAR processing. Against this background, the optical processing method based on the optical 4f system is introduced into SAR imaging. A spatial light modulator (SLM) is placed on the input surface and spectrum surface of the 4f system to load the echo data of the SAR and the matched filter function of the SAR. Using optical Fourier transform to realize the core calculation of SAR data processing can solve the difficulty of processing time-consuming due to the large amount of calculation. In the process of Fourier transform, instead of using a solid glass lens, we use a phase-type Fresnel lens diagram in the SLM to realize the function of Fourier, which avoids the need for special design of Fourier lens. It also greatly reduces the volume and weight of the whole machine, which provides a reference method for real-time imaging of spaceborne SAR.

A NEW DISTRIBUTED TARGET EXTRACTION METHOD FOR POLARIMETRIC SAR CALIBRATION

Abstract. Polarimetric calibration is one of the preprocessing steps in the quantitative processing of Polarimetric synthetic aperture radar (PolSAR) data, and its accuracy will affect subsequent applications. At present, the polarimetric calibration method based on distributed targets is widely used, and this kind of method needs to extract distributed targets that satisfy certain scattering characteristics as the calibration reference ground object samples before calibrating. Therefore, the extraction accuracy of distributed targets has a great influence on the accuracy of polarimetric calibration methods based on such targets. Therefore, this paper proposes a new distribution target extraction method, which is based on the idea of KS hypothesis testing, and uses the homogeneity of the pixels in the window to determine whether it is a distribution target. To verify the effectiveness of the method, the X-band airborne PolSAR images are used as the data of the polarimetric calibration experiment. Experiments show that, compared with other extraction methods, our method can not only ensure the extraction accuracy of distributed targets, but also further improve the accuracy of polarimetric calibration.

Constrained Optimization of FPGA Design for Spaceborne InSAR Processing

With the development of spaceborne processing technologies, the demand for on-board processing has risen sharply. Against this background, spaceborne Interferometric Synthetic Aperture Radar (InSAR) processing has become an important research area. In many cases, high processing capacity is required during on-board InSAR processing, yet Field-Programmable Gate Array (FPGA) resources on the satellites are limited. To improve the performance of spaceborne remote sensing processing, this paper designs a high-performing FPGA system for the coarse registration and interferogram generation process of InSAR. Moreover, to address this dual-constraint problem of resource and processing capacity, the paper proposes an FPGA design method based on the gradient descent theory, which can identify the optimum trade-off scheme between two such constraints. Finally, the proposed system design and method are implemented in FPGA. Experiments showed that the FPGA system outperformed the NVIDIA (Santa Clara, CA, USA) GTX Titan Black Graphics Processing Unit (GPU), and the optimum trade-off scheme only increases the entire time by 1.1% but reduces the FPGA BRAM usage by 8.7%. The experimental results proved the effectiveness and validity of the proposed system and method.

Airborne Elevation DBF-TOPS SAR/InSAR Method Based on LOS Motion Compensation and Channel Error Equalization

Digital beamforming (DBF) TOPS SAR in elevation is a new synthetic aperture radar (SAR) system, which has the advantage of wide swath coverage and a high signal-to-noise ratio (SNR). In this paper, considering the phase preservation demand for interferometric SAR (InSAR) processing, the complete processing chain for DBF-TOPS SAR/InSAR in elevation is proposed with a wide beam angle and channels’ amplitude and phase errors. Firstly, we analyze the airborne motion compensation method along the line-of-sight direction for TOPS SAR with squint angle. Furthermore, for the large-range beam angle of DBF, the sub-swaths division process is presented for the range-dependent radar look angle, and the sub-swaths division criterion is also given in the analytic expression. Then, the relative amplitude and phase errors’ estimation and compensation method between channels is provided in the range frequency domain based on the pivoting filter with coherence weighting, which is convenient for DBF processing and SNR improvement. Finally, the DEMs are generated under different conditions to compare the phase preservation performance. The effectiveness of the proposed processing chain is verified with both simulated data and airborne real DBF-TOPS SAR/InSAR data.

Spaceborne InSAR mapping of landslides and subsidence in rapidly deglaciating terrain, Glacier Bay National Park and Preserve and vicinity, Alaska and British Columbia

The Glacier Bay area in southeastern Alaska and British Columbia, encompassing Glacier Bay National Park and Preserve, has experienced rapid glacier retreat since the end of the Little Ice Age in the mid-1800s. The impact that rapid deglaciation has had on the slope stability of valley walls and on the sedimentation of fans and deltas adjacent to fjords and inlets is an ongoing research topic. Using 3-year (2018–2020) Sentinel-1 datasets, and an automated time-series persistent scatterer interferometric synthetic aperture radar (PSInSAR) processing method, we detected landslides or delta subsidence at 27 sites within a vast 180 × 180 km remote region encompassing Glacier Bay proper. Most of the sites that we identified had not been previously identified. We categorized the hazard source areas that we identified into three general types:1) slow-moving landslides on steep rocky slopes not near (> 2 km away from) present-day glacier termini (e.g., Tidal Inlet landslide), 2) slow-moving landslides directly adjacent to (< 2 km away from), and associated with glacier thinning and retreat, and 3) subsidence of glacial outwash fan deltas. In categories 1 and 2, we observed 22 landslides moving at velocities ranging from 0.5 to 4 cm/yr. In category 3, we detected five fan deltas subsiding at velocities ranging from 0.5 to 6 cm/yr. Within our measurement error, these velocities were consistent during the monitoring period. Because acceleration was not observed, the issuance of warnings of imminent rapid failure is not warranted, however, continued remote monitoring is warranted. Our interferometric synthetic aperture radar (InSAR) results could be combined with other data sets including field observations, subaerial and submarine landslide inventories, bedrock fabric mapping from newly available light detection and ranging (lidar) data, and geologic maps to produce an inherent susceptibility map for landslides in bedrock and fan deltas. This map could be used to forecast susceptibility for both earthquake and climatically induced landslides.

Sensing the Urban Environment by Automotive SAR Imaging: Potentials and Challenges

In this paper, we discuss the possibility of generating high-resolution mapping of urban (or extra-urban) environments by the application of synthetic aperture radar (SAR) processing concepts to the data collected by mm-wave automotive radars installed on-board commercial vehicles. The study is motivated by the fact that radar sensors are becoming an indispensable component of the equipment of modern vehicles, being characterized by low cost, good performance, and affordable processing; therefore, in the future, nearly every single vehicle could be potentially equipped with radar devices capable of high-resolution imaging, enabled by application of SAR processing methodologies. Throughout this paper, we aim to discuss the role of SAR imaging in the automotive context under a theoretical and experimental perspective. First, we present the resulting benefits in terms of angular resolution and signal-to-noise ratio. Then, we discuss relevant technological aspects, such as suppression of angular ambiguities, fine estimation of platform motion, and SAR processing architectures, and we present a preliminary evaluation of the required computational costs. Finally, we will present a number of experimental results based on open road campaign data acquired using an 8-channel MIMO radar at 77 GHz, considering the cases of side-looking SAR, forward SAR, and SAR imaging of moving targets.

Novel optimal time selection method for synthetic aperture radar data processing via expectation‐maximization algorithm

A novel optimal time selection method for synthetic aperture radar (SAR) data processing via the expectation-maximization (EM) algorithm is proposed, which can reduce the computational complexity and improve the image quality simultaneously. First, the Doppler frequency feature after the SAR processing is analyzed from the point of probability. Then, the Doppler frequency is modelled as the Gaussian mixture model (GMM), and the issue of optimal time selection can be implemented by the parameter estimation of GMM. The results of simulated and real measured data are given to demonstrate the effectiveness of the proposed method.

Design and Implementation of Synthetic Aperture Radar (SAR) Field-Programmable Gate Array (FPGA)-Based Processor

Synthetic aperture radar (SAR) is a unique imaging radar system that is capable of obtaining high-resolution images by using signal-processing techniques while operating in all weather and in the absence of a light source. The potential of SAR in a wide range of applications has led to new challenges in digital SAR processor design. On-board storage of SAR raw data is often not practical for real-time applications. The design of digital SAR processors is always restricted by the available space of the carrier system, data transfer rate, payload capacity and on-board power supplies. As reported in the literature, although customized hardware solutions could offer the desired performance, they are not feasible for low-volume production. This research aims to design and develop an efficient digital SAR processor by using field-programmable gate array (FPGA) with the consideration of hardware resources, processing speed and precision. In this paper, a hardware implementation of an FPGA-based SAR processor is presented. The implementation and architecture of the proposed SAR processor are highlighted in this paper. A MATLAB-based SAR processing range-Doppler algorithm (RDA) was developed as the benchmark for the development of an SAR processor. The target device, Altera Stratix IV GX FPGA EP4SGX230KF40C2, was selected for the design and implementation of an FPGA-based SAR processor. Comprehensive evaluations of the performance of the proposed SAR processor in terms of precision, timing performance and hardware resource utilizations are also presented. The proposed FPGA-based digital SAR processor achieves optimum performance in processing SAR signals for image formation. Evaluation shows that the designed SAR processor is capable of processing SAR images with ±1% difference error as compared to SAR images processed by MATLAB. The results also show a reduction in hardware usage via the implementation of an FPGA-based FFT/IFFT coprocessor. These promising results prove that the performance of the proposed processor is satisfactory and the achieved processing time, as well as the power consumption of the processor, outperformed existing implementations.

Spatially Variable Phase Filtering Algorithm Based on Azimuth Wavenumber Regularization for Bistatic Spotlight SAR Imaging Under Complicated Motion

The 2-D space variance of echo signals is the key problem of image processing for bistatic synthetic aperture radar (BiSAR) under nonlinear platform trajectories. Although there are some existing studies that present solutions to deal with space variance under linear or low-order motion, this problem is more severe when the trajectories are more complicated and the imaging scene sizes are larger. To deal with this challenging problem, this article proposes a new imaging method based on a novel azimuth-regularized wavenumber mapping and a highly efficient spatially variable phase filter. The novel wavenumber mapping as the major novelty of the method can simultaneously realize range–azimuth decoupling and coarse focusing in the space domain for all the targets. What is more, the phase function of the echo signal in the wavenumber domain is analytically expressed as a binary polynomial by deriving the inverse mapping of the wavenumber with respect to range frequency and azimuth time. Then, the spatially variable filter is designed based on the analytical expression and realized by upgrading the parameters along the azimuth direction. The filtering process has low complexity and can be executed in parallel for every cross-azimuth cell. Moreover, an algorithm for constraining the residual phase error is presented to guarantee both the efficiency and the accuracy of the image processing. Verified by numerical simulations, the proposed imaging method achieves a superior focusing effect than the existing method that is designed for BiSAR with highly maneuvering platforms while having lower computational complexity.

High-Resolution Real-Time Imaging Processing for Spaceborne Spotlight SAR With Curved Orbit via Subaperture Coherent Superposition in Image Domain

With the increasing of application requirements, the high-resolution real-time imaging processing of the spaceborne spotlight synthetic aperture radar (SAR) has been developed. Since the traditional real-time imaging algorithms have the problems that the range model has errors and the two-dimensional (2-D) space-variance of the equivalent velocity caused by the curved orbit cannot be effectively eliminated. Thus, this article proposes a high-resolution real-time imaging algorithm for spaceborne spotlight SAR with curved orbit via subaperture coherent superposition in image domain. In this article, the echo data are first divided into subapertures to avoid the azimuth spectrum aliasing. After that, the 2-D space-variance of the equivalent velocity caused by the curved orbit can be eliminated by the method of azimuth time scale transformation, higher order phase compensation, and introducing phase transition function. Then, the dechirp function is applied for the subaperture signals to obtain the partial-resolution subaperture images. Finally, these partial-resolution subaperture images are coherently superposed in the image domain to obtain the final full-resolution image of the whole echo data. Moreover, the proposed algorithm improves the real-time performance by adopting the idea that the subaperture data recording and subaperture real-time imaging processing are synchronized, which greatly accelerates the acquisition of the final full-resolution imaging result. At the end of this article, the simulations and the real-time performance analysis are performed to validate the proposed algorithm.

Application of Optimized Grey-Markov Model to Land Subsidence Monitoring With InSAR

Land subsidence prediction in mining areas is one of the most important applications of land deformation monitoring, which is significance for safe production. We used interferometric point target analysis (IPTA) timing series interferometry synthetic aperture radar (InSAR) processing technology to analyze the land subsidence results for the Xinfa mining area from 2017 to 2020; and compared them to global positioning system (GPS) static monitoring data. We proposed a residual correction theory based on deviation coefficient using the grey prediction and Markov models, and an optimized Grey-Markov model (RGM-M model) was established to predict the land subsidence of the mining area. Our results show that: (1) The maximum difference between InSAR timing processing results and GPS monitoring data in the same period is 10.91mm; they have roughly the same subsidence trend, indicating that IPTA timing series InSAR technology are strongly reliable in mining deformation. (2) Compared to the traditional Grey-Markov model, the improved residual correction and dynamic assignment of the Grey-Markov model improves the prediction accuracy. The optimized residual correction and dynamic empowerment of the Grey-Markov model prediction results are more suitable for the actual fluctuation of land subsidence value in the mining area. The maximum root mean square error of the prediction results is 0.751mm, and the maximum average absolute percentage error is 7.46%, which has a certain guiding significance for the work of monitoring, prediction and safety management of land deformation in the mining area.

Synthetic Aperture Radar Image Formation and Processing on an MPSoC

Satellite remote sensing acquisitions are usually processed after downlink to a ground station. The satellite travel time to the ground station adds to the total latency, increasing the time until a user can obtain the processing results. Performing the processing and information extraction onboard of the satellite can significantly reduce this time. In this study, synthetic aperture radar (SAR) image formation as well as ship detection and extreme weather detection were implemented in a multiprocessor system on a chip (MPSoC). Processing steps with high computational complexity were ported to run on the programmable logic (PL), achieving significant speed-up by implementing a high degree of parallelization and pipelining as well as efficient memory accesses. Steps with lower complexity run on the processing system (PS), allowing for higher flexibility and reducing the need for resources in the PL. The achieved processing times for an area covering 375 km <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> were approximately 4 s for image formation, 16 s for ship detection, and 31 s for extreme weather detection. These developments combined with new downlink concepts for low-rate information data streams show that the provision of satellite remote sensing results to end users in less than 5 min after acquisition is possible using an adequately equipped satellite.

Efficient Fast Time-Domain Processing Framework for Airborne Bistatic SAR Continuous Imaging Integrated With Data-Driven Motion Compensation

Fast factorized back-projection (FFBP) is a classic fast time-domain algorithm (FTDA), which is not limited by the assumption of azimuth-invariant of echo signal and is suitable for the bistatic synthetic aperture radar (BiSAR) process of arbitrary geometric configuration. However, when the conventional FFBP processing is employed for continuous imaging of multiple full-apertures, the processing efficiency will be decreased significantly, and difficulty will be introduced in motion compensation (MOCO) development. The main contributions in this article include the following two aspects: 1) a new FTDA framework based on FFBP implementation is developed for continuous imaging where echo data are divided into several full-aperture data blocks and then processed separately by FFBP implementation to reduce redundant BP operations for achieving high efficiency and 2) an efficient and effective data-driven MOCO methodology is developed based on the new FTDA framework for high focusing quality. In MOCO, because the phase error functions of subimages are estimated in the phase history domain from different local polar coordinate systems, these phase error functions are actually discontinuous in the spatial domain, which will bring significant discontinuity and defocusing into the final image. To address this problem, the correspondence of error functions between the spatial domain and the wavenumber domain is revealed based on which the phase error functions are reconstructed to remove the discontinuity for high focusing quality. Promising results from both simulation and raw data experiments are provided and analyzed to validate the high performance of the proposed algorithm.

Location of Synthetic Aperture Radar Imagery via Range History

Geolocation is one of the key synthetic aperture radar (SAR) image processing procedures in SAR-based remote sensing applications. The conventional SAR imagery geolocation model is based on the range-Doppler (RD) equation, which is derived from the Fresnel approximation of SAR. Currently, there is no other rigorous geolocation model for modern high-resolution SAR; however, this approximation may not be fully applicable for various modern SAR imaging modes and algorithms. This study aims to develop a novel SAR image geolocation model based on the SAR range history (RH) equation, which is derived from the basic SAR backscattered signal property. Moreover, a new geometric calibration model is presented for RH-based location. Experiments based on real spaceborne SAR data are presented as examples, and the location accuracy of RH and RD location models are compared. The results show that the location accuracies of the RH and RD models are consistent under the existing SAR processing framework, but those for the RH model demonstrate better performance in the azimuth direction. In theory, the proposed RH model can be used for SAR image products generated from complex modes and non-Fresnel-approximation-based imaging algorithms, making it suitable for future SAR systems.

Fusion of Target and Shadow Regions for Improved SAR ATR

Synthetic aperture radar (SAR) systems, which operate under a slant-viewing geometry, inevitably entail shadow regions in the resulting radar image. Such shadow profiles contain backprojected signatures of an object’s configuration as with target profiles; however, they are rarely utilized in current SAR-based recognition techniques. A major challenge in leveraging shadow information together lies in the intrinsic limitation of current single-pathway approaches, in which the target and shadow cannot be addressed simultaneously because of their incompatible domain properties. Hence, we herein propose novel solutions that enable the successful fusion of target and shadow regions within SAR for the first time. First, we devise new image preprocessing techniques specifically customized for shadows to compensate for their unique domain characteristics, which are distinct from the target. Second, we introduce a parallelized SAR processing mechanism such that a network can independently extract features oriented toward each conflicting modality. Third, adaptive fusion strategies are proposed for the optimal integration of features from each region while considering their relative significance layer by layer. Extensive experiments on public benchmark datasets demonstrate that the proposed framework allows a network to effectively employ shadow signatures and targets, thereby outperforming previous methods significantly for all setups.

An Efficient Full-Aperture Approach for Airborne Spotlight SAR Data Processing Based on Time-Domain Dealiasing

The two-step approach (TSA) is an efficient full-aperture method to solve the Doppler spectrum aliasing when processing data acquired by a synthetic aperture radar (SAR) system operating in beam steering mode. This simple approach solves the spectral aliasing by implementing an azimuth convolution between the raw data and a chirp signal, thus avoiding complex subaperture division and recombination of subaperture approaches. However, as aliasing reoccurs in the slow time-domain after the convolution, the estimation and compensation for residual motion error by autofocus cannot be performed immediately, which is crucial for airborne and high-resolution spaceborne SAR processing. The extended TSA solves this problem by implementing full-aperture azimuth scaling, but it is inefficient when the scaling factor deviates from unity severely, which is common in the data acquisition geometry of an airborne SAR. Aiming at addressing the existing shortcomings, this article combines the TSA with autofocus by the time-domain dealiasing and provides an efficient full-aperture processing framework of airborne spotlight SAR data. Simulated and experimental airborne spotlight SAR data with the transmission signal bandwidth of 1.2 GHz and a coherent integration angle of 15<inline-formula><tex-math notation="LaTeX">$^\circ$</tex-math></inline-formula> are processed by the proposed algorithm and the clarity of the processed results shows its effectiveness.

The Extended Timing Annotation Dataset for Sentinel-1—Product Description and First Evaluation Results

This paper introduces the extended timing annotation dataset (ETAD) product for Sentinel-1 (S-1) which was developed in a joint effort of German Aerospace Center (DLR) and the European Space Agency (ESA). It allows to correct range and azimuth timing of S-1 images for geophysical effects as well as for inaccuracies in synthetic aperture radar (SAR) image focusing. In combination with the precise orbit solution, these effects determine the absolute geolocation accuracy of S-1 SAR images and the relative collocation accuracy of repeat pass image stacks. ETAD contains the gridded timing corrections for the tropospheric and ionospheric path delays, the tidal-based surface displacements, and the SAR processing effects, all of which are computed for each data take using standard models from geodesy and auxiliary atmospheric data. The ETAD product helps S-1 users to significantly improve the geolocation accuracy of the S-1 SAR products to better than 0.2 m and offers a potential solution for correcting large scale interferometric phase variations. The product layout and the product generation are described schematically. The paper also reports first results for different SAR techniques: first, the improvement in geolocation accuracy down to a few centimeters by verification of accurately surveyed corner reflector positions in the range-azimuth plane; second, the well-established offset-tracking technique, that is used for systematic ice velocity monitoring of ice sheets and glaciers, where ETAD can reduce velocity biases down to sub-centimetric values; and third, the correction of atmospheric phase contributions in wide-area interferograms used for national and European ground motion services. These early results proof the added value of the ETAD corrections and that the product design is well suited to be integrated into the processing flows of established SAR applications such as absolute ranging of targets, speckle/feature tracking and interferometry.