Preprint Article Version 1 This version is not peer-reviewed

High-Resolution Spaceborne SAR Geolocation Accuracy Analysis and Error Correction

Version 1 : Received: 1 October 2024 / Approved: 1 October 2024 / Online: 1 October 2024 (14:21:18 CEST)

How to cite: Li, F.; Zeng, Q. High-Resolution Spaceborne SAR Geolocation Accuracy Analysis and Error Correction. Preprints 2024, 2024100071. https://doi.org/10.20944/preprints202410.0071.v1 Li, F.; Zeng, Q. High-Resolution Spaceborne SAR Geolocation Accuracy Analysis and Error Correction. Preprints 2024, 2024100071. https://doi.org/10.20944/preprints202410.0071.v1

Abstract

High-accuracy geolocation is crucial for high-resolution spaceborne SAR images. Most advanced SAR satellites have better theoretical geolocation accuracy than 1 meter but maybe unrealizable with less accurate external data, including the atmospheric parameters and the ground elevations. To investigate the actual SAR geolocation accuracy in common applications, we analyze the properties of different geolocation errors, propose a set of geolocation procedures, and conduct experiments on TerraSAR-X images and a pair of Tianhui-2 images. The results show that based on GNSS elevations, the geolocation accuracy is better than 1 meter for TerraSAR-X and 2 meters / 4 meters for the Tianhui-2 reference / secondary satellite. Based on the WorldDEM and the SRTM, an extra geolocation error of 2 and 4 meters will be introduced, respectively. By comparing the effectiveness of different tropospheric correction methods, we find that the GACOS mapping method has advantages in terms of resolution and computational efficiency. We conclude that the tropospheric error and the ground elevation error are the primary factors influencing the geolocation accuracy, and the key to improving accuracy is to use higher-accuracy DEMs. Additionally, we propose and validate a geolocation model for the Tianhui-2 secondary satellite.

Keywords

SAR geolocation; tropospheric correction; TerraSAR-X; Tianhui-2

Subject

Environmental and Earth Sciences, Remote Sensing

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