摘要
为了提高无人机(UAV)的作战效率和生存概率,在UAV执行任务前,必须为其设计高效的飞行航路。采用将贝叶斯网络模型威胁强度评估算法与蚁群算法相结合的航路规划方法,根据UAV航路规划问题的特点对蚁群算法进行改进。仿真结果表明,该方法能更好地满足实时战场需要,得到良好的优化航路。
In order to improve operational efficiency and survival probability of Unmanned Air Vehicle（UAV）, efficient route must be designed before the UAV performs a mission. This paper uses route planning method which combines the threat intensity assessment algorithm for Bayesian network model and ant colony algorithm. Ant colony algorithm is improved according to characteristic of UAV route planning. Simulation results show that this method can satisfy the needs of real-time battlefield better and get a favorable optimized route.
出处
《计算机工程》
CAS
CSCD
北大核心
2009年第12期175-177,共3页
Computer Engineering
基金
国家自然科学基金资助项目(60374031)
青岛科技大学科研启动基金资助项目(0022147)
关键词
贝叶斯网络
评估算法
威胁强度
蚁群算法
Bayesian network
assessment algorithm
threat intensity
ant colony algorithm
