摘要
根据动态火力分配中"动静结合"的思想,建立了一种带毁伤概率门限的火力分配模型。针对协同空战的第一阶段,在求得对目标机群最大毁伤效果的同时尽量节约导弹武器资源,以应对下一阶段的火力分配。根据粗粒度的并行策略,采用OpenMP并行优化技术对蚁群系统(ACS)中最耗时的循环迭代、循环赋值部分进行并行化处理,在此基础上,将优化后的蚁群算法应用到空战火力分配中,通过对各种规模的火力分配问题进行仿真实验,并验证所提出的火力分配模型的合理性和并行蚁群算法的有效性。
According to the idea of ＂dynamic and static combination＂ in dynamic weapon-target assignment problem,aiming at the first phase of the cooperative air combat,while giving the targets the most damage effect at the same time,trying to save weapon resources as far as possible.In response to the next phase of fire distribution,based on coarse granularity parallel strategy and using OpenMP parallel optimization technique,cyclic iteration and cyclic assignment,which is the main time-consuming part of ant colony system are taken,into parallel processing.Through the simulation of various fire allocation problem,verify the proposed weapon-target assignment model is reasonable,and the parallel ant colony algorithm is effective.
出处
《传感器与微系统》
CSCD
北大核心
2013年第1期20-24,共5页
Transducer and Microsystem Technologies
关键词
静态火力分配
毁伤概率门限
并行蚁群算法
OPENMP
粗粒度策略
static weapon-target assignment
threshold of damage probability
parallel ant colony algorithm
OpenMP
coarse-grained strategy
