针对旋翼式无人机视觉着陆过程中位姿估计精度低、适用距离小的问题，研究了一种基于分级合作目标的融合位姿估计方法。首先，通过分级合作目标的质心相同和固定面积比等属性确定目标区域，并利用LSD直线提取方法获取特征点坐标信息。然后，利用Tsai方法与快速四点方法的融合方法进行无人机位姿参数估计。实验结果表明，分级合作目标增大了无人机位姿估计的适用距离，且该融合方法提高了位姿参数估计精度。

A fusion algorithm of pose estimation based on hierarchical cooperation objective is studied for visual landing of the rotor UAVs. First, the target area is determined by using the properties of the cooperation objectives that they have the same mass center and the fixed area ratio. Then, the LSD line extraction method is used to get the coordinates of the feature points. The Tsai algorithm is used together with fast four-point estimate algorithm to estimate the position and attitude of the UAV. Experimental results show that the hierarchical objective can increase the application range of position estimation and improve the precision of pose estimation.