Polarimetric Synthetic Aperture Radar (PolSAR) calibration is an essential preprocessing step that must be performed to ensure that the data quality is adequate. This, in turn, helps to minimize the propagation of errors in any further data processing or information extraction. Crosstalk and channel imbalance are two major distortions found to be present in the uncalibrated polarimetric SAR data. The PolSAR calibration mainly aims to reduce these two distortions revealing the true scattering pattern of the targets. In this regard, Quegan's algorithm and Ainsworth algorithm are two widely used algorithms for the PolSAR calibration. In this study, the accuracy and efficiency of these two algorithms have been thoroughly compared using suitable metrics. It has been shown that the Ainsworth algorithm performs better than Quegan's in terms of accuracy at the cost of poor computational efficiency. The data quality metrics also highlight the better calibration accuracy of the Ainsworth algorithm. The issue of higher computational complexity has been effectively addressed by coupling both of these algorithms. Evidently, the computational cost has been reduced in the case of the proposed algorithm. The polarization orientation angle (POA) shift is another distortion caused by the topographic variations present in the target scene. Therefore, correction of POA shift has been incorporated in this research by coupling it with the PolSAR calibration. Subsequently, the improvement in the scattering has been observed. In essence, the proposed algorithm coupled with the correction of POA shift rectifies the major polarimetric distortions with adequate accuracy and computational efficiency.

中文翻译：

---

一种高效计算的混合框架，可对四极SAR数据进行极化校准

极化合成孔径雷达（PolSAR）校准是必不可少的预处理步骤，必须执行以确保数据质量足够。反过来，这有助于最小化任何进一步的数据处理或信息提取中的错误传播。串扰和通道不平衡是未校准的极化SAR数据中发现的两个主要失真。PolSAR校准的主要目的是减少这两种失真，从而揭示出目标的真实散射图样。在这方面，Quegan算法和Ainsworth算法是用于PolSAR校准的两种广泛使用的算法。在这项研究中，这两种算法的准确性和效率已使用合适的指标进行了彻底比较。结果表明，Ainsworth算法的性能优于Quegan' 以准确性为单位，以牺牲较差的计算效率为代价。数据质量指标还强调了Ainsworth算法的更好的校准精度。通过结合这两种算法，有效地解决了较高的计算复杂性问题。显然，在所提出的算法的情况下，计算成本已经降低。极化取向角（POA）偏移是由目标场景中存在的地形变化引起的另一种失真。因此，通过将其与PolSAR校准耦合，可以将POA偏移的校正纳入本研究。随后，已经观察到散射的改善。在本质上，