多云天气条件下的大气偏振光定向方法

针对多云天气情况下传统的偏振光定向算法精度下降的问题，提出了一种用于多云天气条件下的大气偏振光定向方法。首先，根据已知信息建立任意一个像素点的偏振光定向模型；然后，基于上一步得到的定向模型，利用随机抽样一致算法筛选出符合要求的内点，并根据筛选出的这些内点得出最符合要求的定向模型；最后，利用选取出的最优的定向模型解算出航向角，实现了基于大气偏振光的定向。通过实际数据证明了该方法的有效性，解算出的航向角误差在少云情况下小于0.5°、多云情况下小于1°。

Atmospheric polarized light orientation method in cloudy weather

Aiming at the problem that the precision of the traditional polarized light orientation algorithm decreases in cloudy weather, this paper proposes a method for atmospheric polarized light orientation in cloudy weather. First, the directional model of polarized light for any pixel is established according to the known information; then, based on the directional model, the interior points that meet the requirements are screened out using the random sampling consistent algorithm, and the most satisfactory directional model is achieved according to the selected interior points; finally, the optimal directional model is used to calculate the heading angle, thereby realizing the orientation via atmospheric polarized light. The validity of the method is proved by the actual data, and the calculated heading angle errors are smaller than 0.5° and 1° in partly cloudy and cloudy weather, respectively.