Improved SAR Radiometric Cross-Calibration Method Based on Scene-Driven Incidence Angle Difference Correction and Weighted Regression

Traditional absolute radiometric calibration methods for synthetic aperture radar (SAR) face challenges in terms of flexibility, maintenance, and calibration frequency. In contrast, radiometric cross calibration can achieve rapid and timely calibration by utilizing the calibrated SAR satellites to illuminate the same ground targets. However, there are still two factors limiting the accuracy of cross calibration. First, two satellites used for cross calibration often have different incidence angles, whereas the existing methods for correcting incidence angle differences have poor performance in scene adaptation and overcorrection. Second, the stability of ground targets plays a critical role in effective cross calibration, but in practice, not all targets possess the same stability. To address the first issue, this article proposes a novel scene-driven incidence angle difference correction method. It leverages the historical information about the target scenes to determine the evaluation threshold for data blocks. Moreover, it incorporates the adaptive exponential cosine model to correct the scattering variations caused by the difference in incidence angle. To address the second issue, an uncertainty analysis method is employed to calculate the uncertainty of each data block. Then, these uncertainties are utilized to calculate weight coefficients, and the calibration constant is determined using a weighted least squares (WLS) model. Cross-calibration experimental results on the Sentinel-1A/B demonstrate an average reduction of 21.6% in the relative calibration error and 18.6% in the root-mean-square error (RMSE) compared with the traditional method, validating the effectiveness of the proposed method.