Evaluation of Geolocation Errors of the Chinese HY-2A Satellite Microwave Scatterometer
The Chinese HY-2A satellite microwave scatterometer (HSCAT) is designed to measure the ocean surface wind vector with a large observation swath. HSCAT is a Ku-band scatterometer that has continuously observing the earth's surface for more than 6 years. Approximately, 30 000 orbit revolutions of...
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Veröffentlicht in: | IEEE transactions on geoscience and remote sensing 2018-10, Vol.56 (10), p.6124-6133 |
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Zusammenfassung: | The Chinese HY-2A satellite microwave scatterometer (HSCAT) is designed to measure the ocean surface wind vector with a large observation swath. HSCAT is a Ku-band scatterometer that has continuously observing the earth's surface for more than 6 years. Approximately, 30 000 orbit revolutions of scientific data are archived in its ground application system. To further understand the characteristics of the instrument, deeper analyses of these scientific data must be carried out. Currently, the geolocation accuracy of the normalized radar cross section (NRCS) has yet to be documented. However, geolocation errors can cause significant measurement bias, and have large impacts on the calibration and validation results. In this paper, the coastline crossing detection method is used to evaluate the geolocation errors of the NRCS data. Some coastal areas and islands where the NRCS data have large gradients are selected for the geolocation error analysis. The coastline inflection points can be identified on the basis that the radar backscatter of land and water exhibits a significant difference when the ocean surface wind speed is relatively low. The longitudes and latitudes of these points from different time periods are then fit to the global self-consistent hierarchical high-resolution shorelines map. The comparison results show that the overall distance error of HSCAT is approximately 2.59 km. This geolocation accuracy meets the instrument design requirements. The sources of geolocation errors are also analyzed in this paper in order to improve the geolocation accuracy. |
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ISSN: | 0196-2892 1558-0644 |
DOI: | 10.1109/TGRS.2018.2832178 |