基于遗传算法的无人机协同侦察航路规划

无人机将成为侦察卫星、有人驾驶侦察机的重要补充与增强手段 ,成为未来战场上广泛应用的一种侦察工具。为了提高无人机 (UAV)的侦察效率 ,在执行侦察任务前必需规划设计出高效的无人机侦察飞行航路。针对这一问题 ,本文提出了一种侦察效率指标评估的计算方法 ,解决了航路规划中的侦察效率量化问题。考虑在大范围任务区域内进行侦察航路优化存在计算的复杂性和收敛性等问题 ,本文采用遗传算法对侦察航路进行了优化处理。通过该方法得到的侦察航路可以有效地提高无人机的侦察效率。

Cooperative Reconnaissance Path Planning For UAV Based on GA Algorithms

UAV will be the supplemental and strengthening way for the satellite and manned aircraft in the reconnaissance missions. They will become the widely used reconnaissance implements in future battle field. To improve the efficiency of the UAV reconnaissance mission, the highly effective path the UAV will fly during the execution of the mission should be planned before the mission carrying out. For the requirement of efficiency, this paper presents a fast method to calculate efficiency index of each path, which solve the quantity problem of the efficiency. Considering the complexity and the convergence problems with the route planning in a large-scale mission area, a genetic algorithm is adopted to deal with the path efficiency planning in this thesis. Simulation results show that the optimal trajectory can maximize the reconnaissance efficiency with ease.