Abstract:

To address the limitations of traditional unmanned aerial vehicle （UAV） path planning algorithms， which often exhibit low efficiency and low success rate of path planning due to inadequate consideration of environmental threats such as terrain elevation， radar detection， and anti-aircraft fire in adversarial scenarios， this paper proposes an improved ARA*-based path planning algorithm for UAVs. The algorithm achieves the integrated calculation of threat factors such as terrain elevation， radar detection， and anti-aircraft fire through the variable weight theory， generates a global 3D gridded threat map， and conducts path planning with an improved ARA* algorithm on the threat map. It incorporates UAV flight performance in path planning constraints for realistic trajectory planning. Simulation experiments demonstrate that the proposed method exhibits excellent adaptability and effectiveness in complex adversarial scenarios， significantly reducing the threat level of planned paths while maintaining a high success rate compared to traditional algorithms. This approach offers a promising solution for enhancing UAV mission completion rates in high-threat environments.

Key words: unmanned aerial vehicle（UAV）, path planning, route planning, threat modeling, variable-weight theory

摘要：

针对传统无人机航迹规划算法寻路效率差，未充分考虑对抗环境下诸如地形高程、雷达探测以及火力威胁等飞行威胁因子导致航迹规划成功率低的问题，提出一种基于改进ARA*的无人机航迹规划算法。通过变权理论综合计算地形高程、雷达探测和火力威胁等威胁因子，形成全局三维网格化的威胁地图；采用改进的ARA*算法在威胁地图上进行路径规划，同时将无人机飞行性能纳入路径规划约束，使其能够规划出符合实际无人机轨迹的路径。仿真实验表明，改进的航迹规划方法在复杂对抗场景下展现出良好的适应性和效果，对比传统算法能够保持航迹寻路高成功率的同时，显著降低规划路径受威胁程度，为无人机在高威胁场景下提高任务完成率提供了一种解决思路。

关键词: 无人机, 航迹规划, 路径规划, 威胁建模, 变权理论