The absolute radiometric accuracy of synthetic aperture radar (SAR) images directly affects the quantitative applications of SAR. It is difficult to continuously monitor SAR systems using conventional calibrator-based methods. However, if a stable backscattering feature can be observed in a common scene, its value can be used as a reference to ensure the routine calibration. In this study, a scattering sample database, which includes several different categories, is built using C-band SAR images, and the analysis of the results depicts that the median center of the backscattering coefficient in urban area is relatively stable over time. Further, a neural network-based method is presented and it can be used to finely filter the urban targets and extract stable backscattering feature. This method is validated by using the test data and a contrast experiment with rainforest data. This further illustrates that the stable feature extracted using this method can be used to perform routine radiometric calibration of SAR systems.
YANG Jintao
,
QIU Xiaolan
,
DING Chibiao
,
LEI Bin
,
LU Xiaojun
. Analyzing and extracting stable feature of target backscattering for C-band SAR[J]. Journal of University of Chinese Academy of Sciences, 2019
, 36(1)
: 115
-124
.
DOI: 10.7523/j.issn.2095-6134.2019.01.016
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