基于梯度粒子群算法的纵横向机动跳跃弹道设计及优化  

Design and Optimization of Vertical Wavy and Crosswise Maneuvering Trajectory Based on Grads Particle Swarm Algorithm

作　　者：鲜勇[1] 李少朋[1] 李振华[1] 刘炳琪[1] 常燕 

机构地区：[1]第二炮兵工程大学七系,西安710025

出　　处：《弹道学报》2015年第3期1-6,共6页Journal of Ballistics

基　　金：国家自然科学基金项目(61304231)

摘　　要：为了增强导弹弹道的机动性能和突防效果,采用2级发动机多次点火及横向机动技术,建立了纵横向机动跳跃弹道模型。针对模型中弹道计算时间长、优化参数多的问题,提出并设计了梯度粒子群算法,将梯度搜索的思想融入到粒子群算法中搜索全局最优解,相应改变微粒速度位置向量的更新方式。仿真结果表明,该算法能够有效地解决纵横向机动跳跃弹道模型的优化问题并具有快速收敛性。To improve trajectory maneuverability and penetration effect, the model of vertical wavy and crosswise maneuvering trajectory was established by using the technology of repeatedly ignition and crosswise maneuvering. In view of more computing time and multiparameter,grads particle swarm algorithm was put forward and devised, and the idea of grads search was blended in the PSO, and the updating model of each particle＇s position and velocity was changed accordingly. The simulation indicates that the vertical wavy and crosswise maneuvering trajectory can be effectively optimized by the algorithm, and the algorithm has fast convergence speed.

关 键 词：机动突防 横向机动 纵向跳跃 优化设计 粒子群算法 

分 类 号：O211.62[理学—概率论与数理统计]