For stealth unmanned aerial vehicles (UAVs), path security and search efficiency of penetration paths are the two most important factors in performing missions. This article investigates an optimal penetration path planning method that simultaneously considers the principles of kinematics, the dynamic radar cross-section of stealth UAVs, and the network radar system. By introducing the radar threat estimation function and a 3D bidirectional sector multilayer variable step search strategy into the conventional A-Star algorithm, a modified A-Star algorithm was proposed which aims to satisfy waypoint accuracy and the algorithm searching efficiency. Next, using the proposed penetration path planning method, new waypoints were selected simultaneously which satisfy the attitude angle constraints and rank-K fusion criterion of the radar system. Furthermore, for comparative analysis of different algorithms, the conventional A-Star algorithm, bidirectional multilayer A-Star algorithm, and modified A-Star algorithm were utilized to settle the penetration path problem that UAVs experience under various threat scenarios. Finally, the simulation results indicate that the paths obtained by employing the modified algorithm have optimal path costs and higher safety in a 3D complex network radar environment, which show the effectiveness of the proposed path planning scheme.

对于隐形无人机（UAV），路径安全性和穿透路径的搜索效率是执行任务的两个最重要因素。本文研究了一种最优的穿透路径规划方法，该方法同时考虑了运动学原理，隐形无人机的动态雷达横截面以及网络雷达系统。通过将雷达威胁估计功能和3D双向扇区多层可变步长搜索策略引入常规A-Star算法，提出了一种改进的A-Star算法，其目的是满足航点精度和算法搜索效率。接下来，使用提出的穿透路径规划方法，同时选择满足雷达系统姿态角约束和rank-K融合准则的新航路点。此外，为了比较分析不同的算法，利用传统的A-Star算法，双向多层A-Star算法和改进的A-Star算法解决了无人机在各种威胁情况下遇到的穿透路径问题。最后，仿真结果表明，在3D复杂网络雷达环境下，采用改进算法得到的路径具有最优的路径成本和较高的安全性，说明了所提出的路径规划方案的有效性。