The aerial docking technology for multirotor drones can address the issues such as limited endurance and small payload capacity， which is of great importance for extending the endurance and improving the task efficiency of multirotor drones. However， the current airborne docking solutions for multirotor drones suffer from high cost and poor docking precision， and are easily affected by environmental constraints. Therefore， this paper proposes an airborne docking solution that integrates monocular vision with an inertial measurement unit （IMU） for positioning， combined with optimal trajectory control， significantly reducing costs while ensuring docking precision. First， the camera identifies and locates the target by AprilTag. Second， it minimizes the reprojection error through nonlinear optimization and employs the error state Kalman filter （ESKF） to more accurately eliminate the IMU bias， improving the accuracy of the fusion positioning. Third， an optimal docking controller is designed based on the linear quadratic regulator （LQR）. Combining the drone’s dynamic model， it directly outputs the attitude control commands for the multirotor drone， achieving safer aerial docking. Finally， experiments are conducted on a quadrotor drone platform and successfully complete the aerial docking task， demonstrating the feasibility of this method.