Abstract
The stability characteristics of scattering are of great significance for achieving radiometric calibration without calibration fields. This letter used dual-polarization synthetic aperture radar (SAR) data to explore the temporal and spatial stability of microwave scattering. Based on Sentinel-1 SAR data, we mainly studied the stability of the median value of SAR image slices in urban areas, under the HH- and HV-polarization modes. The urban slices with stable scattering were extracted by an improved deep neural network designed herein. Based on 33 images of the Houston region, the results show that this suitable network, which is trained by dual-polarization data, can effectively distinguish the stable slices from the unstable ones. In addition, some meaningful characteristics about SAR scattering stability of dual-polarization data are also obtained, which can provide a good reference for SAR nonfield radiometric calibration.
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