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研究了一种紧耦合INS/视觉相对位姿测量方法在无人机自主空中加油中的应用。该方法直接将特征点的图像坐标作为滤波器输入,避免了求解复杂的非线性位姿方程,尤其是特征点提取不全时,该方法具有较强的鲁棒性。引入相对惯导误差建立了增广状态模型,根据杆臂效应详细推导了紧、松两种耦合模式的量测方程。采用扩展卡尔曼滤波算法估计误差状态,并校正惯导输出获取精确的相对位姿信息。仿真结果表明,与松耦合模式相比,紧耦合在提高系统实时性的同时可获得更高的测量精度,位置误差小于0.1 m,姿态角误差小于3’。
The application of a tightly coupled INS / vision relative pose measurement method to autonomous air refueling of UAVs was studied. This method directly uses the image coordinates of the feature points as the input of the filter, which avoids solving the complex nonlinear pose equations. Especially when the feature points are not fully extracted, this method is robust. The relative inertial error is introduced to establish the augmented state model, and the measurement equations of tight coupling and loose coupling are deduced in detail according to the lever arm effect. An extended Kalman filter algorithm is used to estimate the error state, and the output of inertial navigation is corrected to obtain the accurate relative pose information. The simulation results show that, compared with the loosely coupled mode, the tight coupling can improve the real-time performance of the system and achieve higher accuracy. The position error is less than 0.1 m and the attitude error is less than 3 ’.