Adrian Schubert

Influence of Atmospheric Path Delay on the Absolute Geolocation Accuracy of TerraSAR-X High-Resolution Products

Two coupled investigations of TerraSAR-X (TSX) high-resolution data are described in this paper: geometric validation, and estimation of the tropospheric path delay using measurements of corner reflectors (CRs) placed at different altitudes but nearly identical ranges. The CRs were placed within Alpine and valley sites in Switzerland, where terrain diversity provides ideal territory for geometric validation studies. Geometric validation was conducted using slant-range complex products from the spotlight and stripmap (SM) modes in ascending and descending configurations. Based on the delivered product annotations, the CR image positions were predicted, and these predictions were compared to their measured image positions. To isolate path delays caused by the atmosphere, six TSX SM scenes ( ~ 35 x 50 km) were examined containing four identical CRs with the same ranges and an altitude difference of ~ 3000 m. The CR arrangement made it possible to verify the annotated TSX atmospheric path delay by comparing the predicted slant range with the slant range obtained by measuring the reflector image coordinates. Range differences between the high- and low-altitude reflectors helped to quantify small variations in the path delay. Both SM and spotlight TSX products were verified to meet the specified accuracy requirements, even for scenes with extreme terrain variations, in spite of the simplicity of the atmospheric model currently integrated into the processor. Small potential improvements of the geolocation accuracy through the implementation of more comprehensive atmospheric modeling were demonstrated.

Estimation of Atmospheric Path Delays in TerraSAR-X Data using Models vs. Measurements

Spaceborne synthetic aperture radar (SAR) measurements of the Earths surface depend on electromagnetic waves that are subject to atmospheric path delays, in turn affecting geolocation accuracy The atmosphere influences radar signal propagation by modifying its velocity and direction, effects which can be modeled. We use TerraSAR-X (TSX) data to investigate improvements in the knowledge of the scene geometry. To precisely estimate atmospheric path delays, we analyse the signal return of four corner reflectors with accurately surveyed positions (based on differential GPS), placed at different altitudes yet with nearly identical slant ranges to the sensor. The comparison of multiple measurements with path delay models under these geometric conditions also makes it possible to evaluate the corrections for the atmospheric path delay made by the TerraSAR processor and to propose possible improvements.

Sentinel-1A Product Geolocation Accuracy: Commissioning Phase Results

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.

COSMO-skymed, TerraSAR-X, and RADARSAT-2 geolocation accuracy after compensation for earth-system effects

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.

Sentinel-1A/B Combined Product Geolocation Accuracy

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.

Terrain-flattened gamma nought Radarsat-2 backscatter

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 systems 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.

SPACEBORNE SAR PRODUCT GEOLOCATION ACCURACY: A SENTINEL-1 UPDATE

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 Sentinel-1A instrument and operational product performance status

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

Geometric performance of ENVISAT ASAR products

We describe validation measurements of the geometric accuracy of ASAR images, measured redundantly via independent methods. Our tests include image (IM), alternating polarization (AP), and wide swath (WS) mode acquisitions over a variety of test sites. ASARs slant range products (IMS/APS) require a slightly different validation methodology than ground range precision (IMP, APP) and medium resolution products (IMM, APM, WSM). A third approach is required for ellipsoid-geocoded products (IMG, APG). The most highly accurate validation is possible with single look complex (SLC) data (IMS and APS products), as all other product types lose resolution during multilooking. For a library of ground control points (GCPs) including map features such as bridges or road intersections, as well as (where available) transponders and corner reflectors, we use surveyed or map-measured position information (together with the delay value in the case of transponders) to solve the zero-Doppler iteration and predict the position of the GCP as an azimuth and slant range coordinate in the radar image. In the case of ground range products (e.g. IMP, APP, IMM, APM, WSM) the predicted slant range value is additionally transformed by a slant to ground range transformation tro determine the predicted image coordinate. The GCP feature is then either measured by inspection of a detected image, or localized automatically within the neighborhood of the prediction. GCPs are measured within the radar geometry image products, derivative geocoded products, and topographic maps, providing their measured map, radar geometry, and nominally geocoded GTC locations. Radar image locations are compared to map reference values and statistics of differences are tabulated. We compare the accuracies of the estimates achievable using transponders and map GCPs. Based on the suite of products (and accompanying orbit information) available to us, we establish a methodology for estimating a preliminary sampling window start time bias. The multiple validation and estimation techniques used ensure robust determination of ASAR geolocation accuracy.

Robustness of wavelet-based stereo matching for variable acquisition geometries using simulated SAR images

It has been shown that digital surface models (DSMs) generated using stereo SAR can be used to ease the phase-unwrapping process during interferometric height model generation. In addition, wider availability of combined stereoscopic and interferometric coverage generated by air- and spaceborne sensors makes the combined use of the two techniques more feasible. This paper describes a series of experiments whereby different stereo acquisition geometries were simulated for an airborne X-band SAR sensor. The product of such a simulation, taking the topography, flight geometry, and local illuminated area into account, is a pair of amplitude images in slant range geometry. The use of such simulations allows rigorous control of error sources. A phase-based, multi-resolution image-matching technique built on the discrete wavelet transform is used to measure the parallax field between simulated image pairs, and a geocoded height map is generated in each case. The robustness of the matching algorithm across variable sensor configurations is thereby determined. Same-side stereo geometry is assumed, as is a typical airborne flight height of 2.8 km. Matching accuracy and the subsequent height accuracy of the DSMs are evaluated by varying the sensor incidence angles and stereo intersection angle. The optimal flight geometry for a test area in Switzerland is determined.