Clouds play an important role in the radiative energy balance of the Earth-atmosphere system. Compared with traditional optical satellite sensors, polarimetric sensors combine multi-angle, multi-polarization, and multispectral information, displaying the advantages of high spatial and temporal resolutions and global coverage. Such remote sensing measurements improve the accuracy of cloud properties retrieval. Due to the observation characteristics of passive satellites, even a tiny variation in position will result in a great change in the observation geometry. A large number of studies have shown that the scattering angle is very crucial for the polarization characteristics retrieval of reflected light. In this study, we analyze the dependence of the remote sensing retrieval implement of different cloud characteristics on the observed scattering angle coverage, considering both ice and water clouds. Three satellite sensors -POLarization and Directionality of the Earth's Reflectance-3/Polarization and Anisotropy of Reflectance for Atmospheric Sciences coupled with Observations from a Lidar (POLDER-3/PARASOL), Directional Polarimetric Camera/ GaoFen-5 spacecraft (DPC/GF-5), and DPC/GF-5(02)were selected to compare their scattering angle coverages and the number of angular measurements at equatorial, middle, and high latitudes. The requirements for angular polarized and nonpolarized observations varied depending on the retrieval of cloud properties. The impact of orbital characteristics and viewing settings was investigated for cloud detection, cloud phase classification, and cloud microphysical properties retrieval. Finally, an analytical model to comprehensively evaluate the effective angular measurements according to the orbital characteristics and viewing settings was developed to facilitate the future design of similar sensors for cloud remote sensing.