【摘要】 为了深入了解大气折射的相关进展，本文从其影响、公式发展以及修正原理等方面进行了介绍。针对大气折射的影响，本文根据研究领域涉及的波段不同，将其划分为应用于光学成像、激光传输和光电跟踪等领域的可见光到红外波段，以及应用于雷达测量和卫星探测等领域的无线电波段。这两个波段在实际处理过程中选取的计算公式是不同的。根据折射率公式的发展历史对折射率公式进行介绍，并指出了各公式的局限性。目前对于前者波段公式的最佳选择是Rüeger学者所总结的公式，而对于后者建议选择ITU-R P.453-13建议书中的无线电折射率公式。最后介绍了获取大气折射率的传统计算方法和光学测量方法。传统计算方法是基于大气模式或气象数据建立的模型，通过公式计算或模型拟合来确定特定区域的折射率。这种方法在单一环境或平均范围内具有一定的准确性。而光学测量方法不需要大气模型作为基础，更不用依赖气象参数，测量结果数据实时性高、更具路径代表性，能弥补一些传统方式的弊端，更符合未来的发展趋势。更多还原

【Abstract】 This paper presents various aspects of atmospheric refraction to gain insight into the advances in this field. It divides the effects of atmospheric refraction into two categories: the visible-to-infrared bands used in research fields such as optical imaging, laser transmission, and optoelectronic tracking and the radio band used in radar measurements and satellite detection. The calculation formulas for these two bands are different in their practical treatment. This paper introduces the refractive index formulas according to the refractive index formula’s development history and points out the limitations of each formula. The current best choice for the former formula is the one summarized by Rüeger scholars; for the latter, it is recommended to choose the radio refractive index formula in the Rec. ITU-R P.453-14. In addition, the relationship between the refractive index of the Earth’s surface and altitude, reference data for the refractive index on a global scale, and statistical distributions for the calculation of the refractive index gradient are given in the recommendation. Finally, traditional calculation methods for obtaining atmospheric refraction and optical observation methods are presented. The former study is based on the modeling of atmospheric patterns or meteorological data, formulae for refractive indices in specific regions, or model fitting to satisfy accuracy in a single environment or on an average scale. The optical measurement method does not need an atmospheric model as a basis, nor does it rely on meteorological parameters. The measurement results of the data are real-time and more representative of the path. It can make up for some of shortcomings of the traditional methods, and is more in line with future development trend of the future.更多还原