基于改进遗传算法的突防突击航线规划
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摘要
歼轰机突防突击是当前航空兵有效的进攻手段之一。为了增加突防突击任务的安全性,提高突防突击任务的成功率,对航线上我方飞机的被击落概率进行建模,利用改进的遗传算法,以被击落概率为适应度函数,以个体与解空间的距离关系为罚函数,寻找最优解,最终得到被击落概率最小的航线;采用约束的最优保存策略进行选择,防止过早收敛,提出可变算术杂交算子,使得变异个体能够有较大概率落在解空间里。结果表明:通过150代的遗传操作,得到拐点为2时的被击落概率最小的航线为O(120.0,550.0)、A(226.2,495.7)、B(345.8,364.3)、T(330.0,180.0),被击落概率为0.019 3。
The attack and strike of fighter planes is one of the effective means of attack for the current air force.In order to improve the safety of penetration flight,and to promote the probability of running task successfully,the probability model of our aircraft being shot down on the airway is built.By improved genetic algorithm,the probability of being shot down as fitness function,and the distance between an individual and solution space as punishment function,the best solution,i.e.the airway with minimum probability of aircraft being shot down,can be found.Constrained optimal save strategy is being used to prevent the solution from early convergence.Variable arithmetic hybrid operator can limit the individual in solution space.As the result,after 150 times performance,the best airway of flight can be gotten as O(120.0,550.0),A(226.2,495.7),B(345.8,364.3),T(330.0,180.0),whose probability of being shot down is 0.019 3.
The attack and strike of fighter planes is one of the effective means of attack for the current air force.In order to improve the safety of penetration flight,and to promote the probability of running task successfully,the probability model of our aircraft being shot down on the airway is built.By improved genetic algorithm,the probability of being shot down as fitness function,and the distance between an individual and solution space as punishment function,the best solution,i.e.the airway with minimum probability of aircraft being shot down,can be found.Constrained optimal save strategy is being used to prevent the solution from early convergence.Variable arithmetic hybrid operator can limit the individual in solution space.As the result,after 150 times performance,the best airway of flight can be gotten as O(120.0,550.0),A(226.2,495.7),B(345.8,364.3),T(330.0,180.0),whose probability of being shot down is 0.019 3.
引文
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[5]刘光宏,刘宝泉.采用进化算法的测量飞机航线规划[J].沈阳理工大学学报,2013,32(4):41-46.Liu Guanghong,Liu Baoquan.Flight planning of TT&C air station based on evolutionaty programming[J].Journal of Shenyang Ligong University,2013,32(4):41-46.(in Chinese)
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[10]McLain T W,Chandle P R,Rasmussen S,et al.Cooprative control of UAV rendezvous[C].Proceedings of the 2001American Control Conference,2001:2309-2314.
[11]Krikpatrick S,Gelett C,Veechi M.Optimization by simulated annealing[J].Science,1983,220(8):671-680.
[12]Kennedy J,Eberhart R.Particle swarm optimization[C].Proceeding of IEEE International Conference,1995:1942-1948.
[13]袁奇伦,谭绍贤.建立雷达探测概率模型的方法[J].情报指挥控制系统与仿真技术,2001,12:28-32.Yuan Qilun,Tan Shaoxian.A method of building the radar detection model[J].Intelligence Command Control System and Simulation Technology,2001,12:28-32.(in Chinese)
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