Abstract
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.
Highlights
The degree to which an Earth-observing remote sensing platform is able to assign accurate geographic positions to the surface features being imaged is referred to as its geolocation accuracy
This paper focuses on the calibration and validation of the geolocation accuracy for S1A SM Single Look Complex (SLC) and Ground Range Detected Fine-resolution (GRDF) image products
Our results presented in the coming sections confirmed that if restituted or even precise Orbital State Vectors (OSVs) files were annotated, the geolocation quality was nearly equivalent to using the corresponding external files, as long as the orbit interpolation was sufficiently reliable
Summary
The degree to which an Earth-observing remote sensing platform is able to assign accurate geographic positions to the surface features being imaged is referred to as its geolocation accuracy. Earth’s surface which can be used for time series analyses, or combined with data from other platforms or sensors For these goals to be feasible, S1A products [2] are required to provide high and consistent geolocation accuracy, as specified in Tables 7-1 through 7-10 of [2]. In addition to orbit- and sensor-specific technical challenges, achieving the highest-possible accuracy from SAR image products requires correcting for at least two perturbing factors [6,7,8]:. As the oceans are periodically redistributed by the relative positions of the Sun-Moon-Earth system, the changing weight distribution of the water mass on the ocean bed causes the Earth to deform These vertical fluctuations usually do not exceed several centimeters for inland sites [9] and are neglected in this study
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