Sentinel-1 (S-1) is the European flagship SAR mission initiated by European Space Agency and the European Commission. It is a constellation of two C-band twins satellite providing backscatter globally. The calibration and overall SAR performance of the mission is continuously assessed by the S-1 Mission Performance Center being a joint venture of European experts in their domain under ESA‘s supervision. This paper addresses the Copernicus Sentinel-1A/B mission’s SAR calibration and overall performance indicators after 8 years cumulated operation having in sight S-1A approaching its expected lifetime of 7 years. Sentinel-1 uses predefined observation scenario to provide a high revisit frequency and systematic global SAR image coverage. This is mainly based upon the operational use of the TOPS (Terrain Observation with Progressive Scans in azimuth) SAR imaging mode allowing to achieve a wide swath with a relatively high resolution. In particular, we present results of the SAR system performance analysis focusing on the instrument stability, the radiometric, geolocation accuracy, the Noise Equivalent Sigma Zero (NESZ) and all interferometric performance indicators. In addition, we discuss the Sentinel-1A/B SAR cross-calibration and the evolution of the system in the near future.

This article shows how the array of corner reflectors (CRs) in Queensland, Australia, together with highly accurate geodetic synthetic aperture radar (SAR) techniques-also called imaging geodesy-can be used to measure the absolute and relative geometric fidelity of SAR missions. We describe, in detail, the end-to-end methodology and apply it to TerraSAR-X Stripmap (SM) and ScanSAR (SC) data and to Sentinel-1 interferometric wide swath (IW) data. Geometric distortions within images that are caused by commonly used SAR processor approximations are explained, and we show how to correct them during postprocessing. Our results, supported by the analysis of 140 images across the different SAR modes and using the 40 reflectors of the array, confirm our methodology and achieve the limits predicted by theory for both Sentinel-1 and TerraSAR-X. After our corrections, the Sentinel-1 residual errors are 6 cm in range and 26 cm in azimuth, including all error sources. The findings are confirmed by the mutual independent processing carried out at University of Zurich (UZH) and German Aerospace Center (DLR). This represents an improvement of the geolocation accuracy by approximately a factor of four in range and a factor of two in azimuth compared with the standard Sentinel-1 products. The TerraSAR-X results are even better. The achieved geolocation accuracy now approaches that of the global navigation satellite system (GNSS)-based survey of the CRs positions, which highlights the potential of the end-to-end SAR methodology for imaging geodesy.

Sentinel-1 (S-1) is a constellation of two C-band SAR satellites [1] whose development is co-funded by the European Space Agency (ESA) and the European Commission (EC) as part of the Copernicus space program. S-1A was launched in May 2014 followed by the S-1B unit two years after. The constellation is operational since September 2016 after the successful commissioning of the second unit. This paper provides an update of the constellation performance and recalls the last result achieved in terms of radiometric and geometric accuracy.

Sentinel-1 A and B are twin spaceborne C-band synthetic aperture radar (SAR) sensors developed and operated by the European Space Agency under the Copernicus Earth Observation programme. An accurate geometric cal-ibration has been performed since the Commissioning Phases on operationally generated Level-1 SAR products. In this paper we address the new improvements to the geometric calibration of Sentinel-1A and -1B products, describing corrections applied to the data to remove artefacts such as swath-dependent biases that had previously been observed in corner reflector measurements.

This paper addresses the Copernicus Sentinel-1A/B mission’s SAR and InSAR performance. Sentinel-1 uses preprogrammed SAR mode operations to provide a high revisit frequency and systematic global SAR image coverage. This is mainly based upon the operational use of the novel TOPS (Terrain Observation with Progressive Scans in azimuth) SAR imaging mode. We present results of the SAR system performance analysis focusing on the instrument stability, the radiometric and geolocation accuracy, as well as the Noise Equivalent Sigma Zero (NESZ). In addition, we discuss the cross- Sentinel-1A/B SAR Interferometry (InSAR) performance considering the effects of burst synchronization and SAR antenna pointing on the achievable common Doppler bandwidth, as well as the obtained InSAR orbital baseline due to the orbital tube maintenance.

Synthetic Aperture Radar (SAR) satellites observe range and azimuth geometric accuracies at the low centimeter level. The accuracy of geolocation is driven by several aspects, e.g. orbit determination, SAR image processing, or atmospheric error correction. Our paper concentrates on the Sentinel-1 mission and the compensation of the platform motion effects in the geolocation, which were found to limit the best possible geolocation capabilities of Sentinel-1. The key to advance the geolocation results is the rigorous compensation of the bistatic effect in azimuth, and the correction of the Doppler-induced shifts in range. First results for Sentinel-1 at the Australian reflector array consisting of 40 Corner Reflector (CR) show consistent improvement in the geolocation $(1\sigma)$ to 6 cm in range and 28 cm in azimuth for both spacecrafts when using the Interferometric Wide swath (IW) product.

This paper addresses the results of the instrument and product performance verification, radiometric and geometric calibration achieved since the end of the respective Sentinel-1 A and B commissioning phases.

The fusion of synthetic aperture radar (SAR) and optical data is a dynamic research area, but image segmentation is rarely treated. While a few studies use low-resolution nadir-view optical images, we approached the segmentation of SAR and optical images acquired from the same airborne platform – leading to an oblique view with high resolution and thus increased complexity. To overcome the geometric differences, we generated a digital surface model (DSM) from adjacent optical images and used it to project both the DSM and SAR data into the optical camera frame, followed by segmentation with each channel. The fused segmentation algorithm was found to out-perform the single-channel version.

Sentinel-1A and -1B are twin spaceborne synthetic aperture radar (SAR) sensors developed and operated by the European Space Agency under the auspices of the Copernicus Earth observation programme. Launched in April 2014 and April 2016, Sentinel-1A and -1B are currently operating in tandem, in a common orbital configuration to provide an increased revisit frequency. In-orbit commissioning was completed for each unit within months of their respective launches, and level-1 SAR products generated by the operational SAR processor have been geometrically calibrated. In order to compare and monitor the geometric characteristics of the level-1 products from both units, as well as to investigate potential improvements, products from both satellites have been monitored since their respective commissioning phases. In this study, we present geolocation accuracy estimates for both Sentinel-1 units based on the time series of level-1 products collected thus far. While both units were demonstrated to be performing consistently, and providing SAR data products according to the nominal product specifications, a subtle beam- and mode-dependent azimuth bias common to the data from both units was identified. A method for removing the bias is proposed, and the corresponding improvement to the geometric accuracies is demonstrated and quantified.

Remote sensing radar satellites cover wide areas and provide spatially dense measurements, with millions of scatterers. Knowledge of the precise position of each radar scatterer is essential to identify the corresponding object and interpret the estimated deformation. The absolute position accuracy of synthetic aperture radar (SAR) scatterers in a 2D radar coordinate system, after compensating for atmosphere and tidal effects, is in the order of centimeters for TerraSAR-X (TSX) spotlight images. However, the absolute positioning in 3D and its quality description are not well known. Here, we exploit time-series interferometric SAR to enhance the positioning capability in three dimensions. The 3D positioning precision is parameterized by a variance–covariance matrix and visualized as an error ellipsoid centered at the estimated position. The intersection of the error ellipsoid with objects in the field is exploited to link radar scatterers to real-world objects. We demonstrate the estimation of scatterer position and its quality using 20 months of TSX stripmap acquisitions over Delft, the Netherlands. Using trihedral corner reflectors (CR) for validation, the accuracy of absolute positioning in 2D is about 7 cm. In 3D, an absolute accuracy of up to \(\sim \)66 cm is realized, with a cigar-shaped error ellipsoid having centimeter precision in azimuth and range dimensions, and elongated in cross-range dimension with a precision in the order of meters (the ratio of the ellipsoid axis lengths is 1/3/213, respectively). The CR absolute 3D position, along with the associated error ellipsoid, is found to be accurate and agree with the ground truth position at a \(99\,\%\) confidence level. For other non-CR coherent scatterers, the error ellipsoid concept is validated using 3D building models. In both cases, the error ellipsoid not only serves as a quality descriptor, but can also help to associate radar scatterers to real-world objects.

This paper provides the status of the Sentinel -1B performance as at a few weeks after launch.

Sentinel-1A (S1A) is an Earth observation satellite carrying a state-of-the-art Synthetic Aperture Radar (SAR) imaging instrument. It was launched by the European Space Agency (ESA) on 3 April 2014. With the end of the in-orbit commissioning phase having been completed at the end of September 2014, S1A data products are already consistently providing highly accurate geolocation. StripMap (SM) mode products were acquired regularly and tested for geolocation accuracy and consistency during dedicated corner reflector (CR) campaigns. At the completion of this phase, small geometric inconsistencies had been understood and mitigated, with the high quality of the final product geolocation estimates reflecting the mission’s success thus far. This paper describes the measurement campaign, the methods used during geolocation estimation, and presents best estimates of the product Absolute Location Error (ALE) available at the beginning of S1A’s operational phase.

This paper addresses the results of the instrument and product performance verification, radiometric and geometric calibration achieved during the since commissioning and routine phase.

Sentinel-1A (S1A), launched by the European Space Agency (ESA) on April 3, 2014, is a state-of-the-art spaceborne Synthetic Aperture Radar (SAR) Earth observation platform. S1A products are expected to provide high and consistent geolocation accuracy. As of the end of May, 2014, the satellite has not yet reached its reference orbit. However, estimation of product geolocation accuracy is ongoing, and improvements are continually being made. The results reported here represent the early situation, with continued progress expected.

The Advanced Synthetic Aperture Radar (ASAR) on- board Envisat operated successfully for just over 10 years until the failure of Envisat in April 2012. ASAR was ESA's very first deployment of a C-band phased- array antenna, allowing extended imaging capacity in comparison to its ERS SAR predecessors. As such it operated in various acquisition modes - Image (IM), Alternating Polarisation (AP), Wide Swath (WS), Global Monitoring (GM), and Wave (WV). For IM and AP modes there was a selection of 7 swaths with swath width from 100 km to 56 km: IM was single- polarisation, while AP was dual-pol, offering a choice from HH&VV, HH&HV, or VV&VH. WS and GM modes had a total swath width of 405 km based on the combination of 5 sub-swaths. WV acquired imagettes of 10 km by 10 km every 100 km along the satellite track. This paper is a look back to the 10 years of ASAR operations, covering topics such as the ASAR Instrument (characteristics, acquisition modes, product tree and observation scenario), Instrument Calibration and Performance Verification (including instrument stability, internal calibration, external calibration, absolute radiometric calibration, localisation accuracy, absolute geolocation accuracy, performance verification and product calibration), ASAR specific missions (wave and polarimetric), particular ASAR events such as

For the observation and monitoring of glacier surface velocity (GSV), remote sensing is an increasingly suitable tool thanks to the high temporal and spatial resolution of the data. Radar sensors have the specific advantage over optical sensors of being nearly weather and time-independent.Two image pairs separated by 11 days, acquired with the high-resolution spotlight (HS) and stripmap (SM) modes of the German sensor TerraSAR-X, were used to estimate GSV over Switzerland's Aletsch Glacier. The SM mode covers larger ground swaths, making it more suitable for glacier-wide observations, while the HS images cover less area but offer the highest-possible spatial resolution, approximately 1 x 1 m on the ground. The images were acquired during the summer to maximise feature visibility by minimal snow cover.GSV estimation was performed using two methods, the comparison of which was a major goal of this study: traditional cross-correlation optimisation and a dense image matching algorithm based on complex wavelet decomposition. Each method was found to have unique advantages and disadvantages, but it was concluded that for GSV monitoring, cross-correlation is probably preferable to the wavelet-based approach. While it generates fewer estimates per unit area, this is not necessarily a critical requirement for all glaciological applications, and the method requires less initial "tuning" (calibration) than the wavelet algorithm, making it a slightly better tool in operational contexts. Also, the use of the highest-resolution spotlight datasets is recommended over stripmap mode images when large-area coverage is less critical. The comparative lack of visible features at the resolution of the stripmap images made reliable GSV estimation difficult, with the exception of several small areas dominated by large crevasses. (c) 2013 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS) Published by Elsevier B.V. All rights reserved.

A Synthetic Aperture Radar (SAR) sensor with high geolocation accuracy greatly simplifies the task of combining multiple data takes within a common geodetic reference system or Geographic Information System (GIS), and is a critical enabler for many applications such as near-real-time disaster mapping. In this study, the geolocation accuracy was estimated using the same methodology for products from three SAR sensors: TerraSAR-X (two identical satellites), COSMO-SkyMed (four identical satellites) and RADARSAT-2. Known errors caused by atmospheric refraction, plate tectonics and the solid-Earth tide were modeled and compensated during the analysis. Of the products analyzed, TerraSAR-X provided the highest absolute and relative geolocation accuracy.

Radarsat-2 offers a variety of new modes and capabilities. We present results from rigorous application of geometric and radiometric calibration to backscatter values, enabling comparisons between different modes. First, the system's a priori geometric accuracy was tested (tiepoint free) by comparing the measured positions of corner reflectors in ultrafine images with predicted locations calculated based on the satellite state vectors and radar timing annotations. Second, the geometric accuracy of the dual-pol ScanSAR SCNB mode was tested by correlating each backscatter image to a radar image simulation calculated using the same product annotations. Third, the radar image simulation was used to normalize the backscatter values in both polarisations, generating terrain-flattened gamma nought values that were then terrain geocoded. Fourth, the available ascending and descending SCNB image pair was overlaid with and without such radiometric terrain correction applied. The advantages gained by using terrain-flattened gamma nought are discussed.