云是指停留在大气层中的水滴或冰晶胶体的集合体，也是地球上庞大水循环产生的有形结果，在全球气候中扮演着重要的角色。偏振遥感对光的辐射强度、方向、相位以及偏振状态等波谱特性进行描述，丰富了观测信息量，提升了观测信息的维度。为了更好地了解偏振遥感云的优势，本文对国际上发射的POLDER、APS、DPC等标志性的偏振传感器的特征和云反演算法进展进行了总结，涉及到相关偏振载荷参数信息、云参量算法的介绍和产品等相关内容，并就经典偏振云参量算法做了详细的总结和评价。随着国际上后续偏振传感器快速增加，对未来偏振传感器的发展方向和相关算法进行了展望。

Clouds are collections of water droplets or ice crystal colloids suspended in the atmosphere. They are a visible manifestation of the Earth’s massive water cycle, which play an important role in global climate. Since the radiation intensity signal cannot accurately detect the internal physical characteristics of thick clouds, especially convective clouds, high-quality cloud observations cannot be achieved only by using this signal. Polarimetric remote sensing can describe the spectral characteristics of intensity, directions, phase positions, and polarization states of light， so as to expand the volumes and dimensions of the information observed. It can detect the size, shape, and other microphysical parameters, showing unique application advantages in cloud remote sensing.A wealth of literature on the development of polarimetric sensors can be found, for example, POLDER launched by France, ASP designed by the United States, and DPC developed by China. This paper summarizes the characteristics of internationally developed landmark polarimetric sensors and introduces the polarimetric sensor that will be launched soon. It is found that the development of polarimetric sensors underwent three main periods. During the first period, polarimetric sensors had low spatial resolution, fewer polarization spectrums, fewer angles, and low polarimetric accuracy. During the second period, the four elements mentioned above have been improved. In the third period, the sensors were developed into products with high spatial resolution, more polarization spectrum, large angles, and high polarimetric accuracy. The accessible spatial resolution, polarization data, and polarimetric accuracy were all greatly improved.In addition, this paper discusses the research on polarization data of cloud detection, physical characteristics, and optical characteristics of clouds. Starting from a series of problems existing in traditional remote sensing observation methods in cloud research, including poor cloud detection of accuracy, physical and optical characteristics, etc., the advantages of polarization detection are revealed through a detailed introduction to the classical polarization cloud parameter algorithms. Moreover, the development history of cloud polarimetric remote sensing research and the critical role played by the application of polarization data in cloud-related studies are explored.By reviewing the development of polarimetric sensors and the evolution of cloud remote sensing algorithms in the past three decades, we found that the polarimetric accuracy, and spatial and time resolution were improved as the number of polarimetric sensors increased. However, the acquired polarimetric signal is increasingly complex. Therefore, when designing the algorithm of cloud remote sensing, the factors we should consider will be fewer. In contrast, the algorithm will be more rigorous, and the inversion accuracy of cloud parameters will be higher. Considering that with the accumulation of experience and the development of instruments, it is believed that the polarization data will make significant progress in optimizing cloud parameters.