针对视线方程中位置和姿态信息存在严重耦合及强非线性的问题，研究了一种相对位姿解耦迭代确定算法，并用于无人机空中加油. 根据卫星导航中的伪距概念，利用视线矢量构建观测矩阵，通过最小二乘法求解相对位置更新，进而更新伪距确定相对姿态. 引入单步迭代误差证明了算法的收敛性，通过分析误差协方差阵的迹讨论
特征点几何构型对相对位置确定精度的影响. 仿真结果表明，与高斯最小二乘微分修正算法相比，提出的算法运行速度和抗噪声性能分别提高了23%和40%，相对位置稳态误差优于0.1 m，相对姿态误差优于0.5±，满足无人机空中加油对接阶段相对位姿测量精度要求.

 Considering the coupled and nonlinear relationship between the relative pose in the line of sight
equations, an iterative decoupling algorithm is proposed to determine relative pose. Application of the method
to aerial refueling is discussed. Based on the pseudo-range of satellite navigation, an observation matrix is
constructed by using line of sight vectors. The relative position are updated by the least square method, and
then the relative attitude is updated. By introducing an iterative error, convergence of the iterative algorithm
is proved. The trace of error variance matrix is used to analyze the effect of feature geometry configuration
on the precision. Simulation results show that the proposed algorithm can improve performance by 23% and
40% in speed and robustness than Gaussian least square differential correction (GLSDC), respectively. Steady
state errors of relative pose are 0.1 m and 0.2± lower respectively. The precisio can satisfy the relative pose
requirements of UAV aerial refueling during docking.