The Polarimetric Synthetic Aperture Radar (PolSAR) systems use electromagnetic radiations of different polarizations in the microwave frequency to collect the scattering information from targets on the Earth. Nevertheless, as with any other electronic device, the PolSAR systems are also not ideal and subjected to distortions. The most important of these distortions are the polarimetric distortions caused due to the channel imbalance, phase bias, and crosstalk between the different polarization channels. For the spaceborne PolSAR systems, the Earth’s ionosphere also contributes to an additional polarimetric distortion known as the Faraday rotation. An effort was made in this study to perform the polarimetric calibration of the Quad-pol and Compact-pol PolSAR datasets acquired using different airborne and spaceborne PolSAR systems to estimate and minimize these polarimetric distortions. The investigation was also done to analyze the impact of these polarimetric distortions on the scattering mechanisms from ground targets and on its dependency on the radar wavelength. The study was done using the UAVSAR L-band Quad-pol dataset, RADARSAT-2 Quad-pol dataset, ALOS-2 PALSAR-2, ISRO's L&S- Band Airborne SAR (LS-ASAR) Quad-pol and Compact-pol datasets, and the RISAT-1 Compact-pol dataset. Calibration of the airborne PolSAR data was carried to understand the level of polarimetric distortions in the LS-ASAR product that is a precursor mission to the spaceborne Dual-Frequency L&S Band NASA-ISRO Synthetic Aperture Radar (NISAR) mission. It is understood that the crosstalk is the dominant polarimetric distortion, which severely affects the PolSAR datasets compared to the other polarimetric distortions, and it is more for the higher wavelength PolSAR systems. The Quegan, Improved Quegan, and Ainsworth algorithms for crosstalk estimation and minimization was performed for the different Quad-pol datasets and it was found that the Improved Quegan algorithm is suitable for removing crosstalk from datasets having high crosstalk and the Ainsworth algorithm is suitable for removing crosstalk from datasets having low crosstalk. The Freeman method of the polarimetric calibration was implemented for the compact-pol datasets and it was able to considerably minimize the polarimetric distortions. The coherency matrix, scattering matrix, model-based decomposition, polarimetric signatures, and roll invariant parameter-based analysis revealed that all the datasets after polarimetric calibration were showing the correct scattering responses expected from the ground targets.

极化合成孔径雷达（PolSAR）系统使用微波频率中不同极化的电磁辐射来收集地球上目标的散射信息。然而，与任何其他电子设备一样，PolSAR 系统也并不理想，并且会出现失真。这些失真中最重要的是由于通道不平衡、相位偏差和不同偏振通道之间的串扰引起的偏振失真。对于星载 PolSAR 系统，地球的电离层也会造成额外的极化失真，即法拉第旋转。本研究努力对使用不同的机载和星载 PolSAR 系统获取的 Quad-pol 和 Compact-pol PolSAR 数据集进行极化校准，以估计和最小化这些极化失真。还进行了调查以分析这些极化失真对地面目标的散射机制及其对雷达波长的依赖性的影响。该研究使用 UAVSAR L 波段 Quad-pol 数据集、RADARSAT-2 Quad-pol 数据集、ALOS-2 PALSAR-2、ISRO 的 L&S 波段机载 SAR (LS-ASAR) Quad-pol 和 Compact-pol 数据集完成，和 RISAT-1 Compact-pol 数据集。对机载 PolSAR 数据进行了校准，以了解 LS-ASAR 产品中的极化失真水平，这是星载双频 L& 的前身任务 S 波段 NASA-ISRO 合成孔径雷达 (NISAR) 任务。据了解，串扰是主要的偏振失真，与其他偏振失真相比，它严重影响了 PolSAR 数据集，并且对于更高波长的 PolSAR 系统更是如此。对不同的 Quad-pol 数据集进行了用于串扰估计和最小化的 Quegan、改进的 Quegan 和 Ainsworth 算法，发现改进的 Quegan 算法适用于从具有高串扰的数据集中去除串扰，而 Ainsworth 算法适用于去除来自具有低串扰的数据集的串扰。极化校准的 Freeman 方法是针对紧凑极化数据集实施的，它能够大大减少极化失真。相干矩阵、散射矩阵、