Abstract: Atmospheric polarization mode supports the polarization navigation application by virtue of the "∞" feature containing the solar meridian information. However, due to the limitation of the physical characteristics of the acquisition device, the surrounding environment of the acquisition location and the occlusion of thin clouds, the obtained atmospheric polarization information is partially distorted and the accuracy of the solar meridian is reduced. In order to solve this problem, this paper proposes an atmospheric polarization pattern generation network based on neighborhood constraints. The network mines the continuity of atmospheric polarization pattern distribution, increases the constraints of reconstruction process through multi-step neighborhood feature reasoning, and accurately generates global atmospheric polarization information from local effective polarization information. In addition, according to the physical characteristics of the atmospheric polarization mode, the angle loss of solar meridian is proposed to further improve the accuracy of the solar meridian. In this paper, experiments are carried out on the measured atmospheric polarization data, and compared with other latest methods. The experimental results show the robustness and superiority of this method.