基于Voronoi图和离散微粒群优化算法的UCAV攻击轨迹决策

根据UCAV可发射区简化模型,提出了UCAV攻击轨迹决策问题。提出了UCAV攻击轨迹决策的分层设计方法,并将其转化为优化问题。首先根据已知的飞行环境,采用Voronoi图生成初始轨迹;然后通过建立攻击轨迹约束条件模型、飞行距离模型和威胁模型,以飞行距离和威胁代价为优化目标函数,构建了UCAV攻击轨迹决策模型,并在此基础上提出了一种离散微粒群优化(Discrete Particle Swarm Optimization, DPSO)算法对攻击轨迹决策模型进行求解。仿真结果表明,通过Voronoi图和DPSO算法能够较好地解决UCAV攻击轨迹决策问题,并能够在多约束条件下对目标函数进行组合优化。

Attack Trajectory Decision-Making for UCAV Based on Voronoi Diagram and DPSO Algorithm

According to simplified model of UCAV launching area, the attack trajectory decision-making for UCAV is introduced. A hierarchical trajectory-designing approach is proposed, and the problem is changed into optimization design. Firstly, the original trajectory is created by Voronoi diagram based on the known flight environment. Secondly, attack trajectory decision making model of UCAV is built based on attack trajectory constraint conditions, flight distance model and threaten model. And the discrete particle swarm optimization is presented to solve it. The simulation results show that DPSO algorithm is simple and can be used to effectively solve the problem of attack trajectory decision-making for UCAV.