基于粒子群算法的新型主动防护系统的拦截效能分析

发布时间：2018-05-07 08:01

本文选题：主动防护系统 + 网状弹药　；参考：《系统工程与电子技术》2017年12期

【摘要】：点对点式拦截来袭目标的拦截概率较低且高度依赖目标探测系统精度和拦截算法解算精度,针对该问题,提出一种新型的主动防护系统拦截来袭目标的方案,即采用姿态可调的牵引体发射网状弹药,形成面对点式的"网"来拦截来袭目标。在分析网状弹药发射方式及拦截来袭目标飞行轨迹的基础上,建立了网状弹药的牵引体的运动模型,将拦截网的运动状态分解至其牵引体的运动状态,以牵引体的空间位置确定拦截网的有效拦截面积,减少了对网姿态计算的复杂性,同时简化高速来袭目标的运动为直线运动。采用遗传算法改进的粒子群算法解决了防护系统的多个发射参数的优化问题,最后采用蒙特卡罗打靶实验方法,仿真分析了影响拦截效能的参数设计问题,为新型主动防护系统的进一步优化设计提供了技术支撑。
[Abstract]:The intercepting probability of point-to-point intercepting incoming target is low and highly dependent on the precision of target detection system and the precision of intercepting algorithm. In order to solve this problem, a new active protection system for intercepting incoming target is proposed. In other words, the towing body with adjustable posture is used to fire the mesh ammunition to form the face point "net" to intercept the incoming target. Based on the analysis of the firing mode of the mesh ammunition and the flight path of the intercepting incoming target, the motion model of the towing body of the mesh ammunition is established, and the motion state of the interceptor network is decomposed to the motion state of the tractor body. The effective intercept area of the interceptor network is determined by the space position of the towing body, which reduces the complexity of the calculation of the attitude of the network and simplifies the movement of the high speed incoming target as a straight line motion. The particle swarm optimization (PSO) improved by genetic algorithm is used to solve the optimization problem of multiple launch parameters of the protective system. Finally, the parameter design problem affecting the interception efficiency is simulated and analyzed by using Monte Carlo shooting experiment method. It provides technical support for the further optimization design of the new active protection system.
【作者单位】：南京理工大学机械工程学院智能弹药技术重点实验室;
【基金】：国家自然科学基金(11172141) 国家高技术研究发展计划(863计划)(2015AA7046411,2015AA7046606)资助课题
【分类号】：E926.4;TP18

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