摘要
为了提高无人机(UAV)的作战效率和生存概率,在执行任务之前必须设计出高效的无人机飞行航路。针对这一问题,采用了蚁群算法进行航路规划,并对蚁群算法进行了改进。提出了保留最优解、自适应状态转换规则和自适应信息激素更新规则,有效的提高了算法算收敛速度和解的性能。最后用改进的蚁群算法对无人机任务航路进行了仿真,仿真结果表明,该算法是一种有效的航路优化算法。
In order to improve operational efficiency and survival probability, the optimal route of an unmanned air vehicle （UAV） should be designed before the UAV performs a mission. For this question, an ant colony algorithm is used and is improved for route optimizing of UAV. Measures of keeping optimization, adaptively selecting and adaptively adjusting are applied, which is a better path at higher convergence speed. Finally the algorithm is implemented, and the results show that it＇s a better path -planning algorithm.
出处
《航空计算技术》
2006年第4期112-114,118,共4页
Aeronautical Computing Technique
