基于UTD和GA混合算法的无人机载天线布局优化

为克服无人机天线之间的相互干扰，采用遗传算法对天线进行优化布局，以减少天线间的耦合。通过采用一种新的目标函数，结合一致性几何绕射理论对圆柱体上的单极子天线和无人机表面上单极子天线的布局进行优化，得到了最佳的优化位置。通过Feko仿真对优化位置结果进行验证，得到了最佳位置处S参数值，可知天线优化位置后相互之间的耦合度变小，这也间接证明了该方法计算的正确性。该方法能够及时准确地对机载天线间的耦合度进行预测和评估，具有实际应用价值。

Layout optimization of UVA airborne antennas based on GA and UTD

In order to overcome the interference of the antenna, the Genetic Algorithm(GA) is used to optimize the layout of the antenna to reduce the coupling between antennas. By using a new objective function, combining with the Uniform geometrical Theory of Diffraction(UTD), layout optimization is performed on the monopole antennas both on the cylinder and on the surface of Unmanned Aerial Vehicle(UAV). The results of location optimization are proved by Feko simulation, and the S parameter values at the best position show that the coupling between antennas becomes smaller after the placement optimization, which also indirectly validates the correctness of the method. This method can be applied to predict and evaluate the coupling degree of the airborne antenna on time and has practical application value.