摘要
针对整个空间体域飞行器三维安全路径的优化问题,提出一种基于稀疏性约束蚁群算法的安全路径规划方法。该方法首先将空间体域划分为栅格,并计算各栅格中由所有雷达探测概率组成的威胁向量,然后对威胁向量进行量化以合成空间威胁值,最后利用稀疏性约束的蚁群算法进行路径规划寻优。仿真结果表明,该文方法可规划出最优的安全路径,并且相对传统蚁群算法,有效减少了搜索时间。
To solve the optimization problem of3D safe route planning for aerospace vehicle in the whole space domain,a sparse-constrained ant colony algorithm is presented for safe route planning.Firstly space domain is divided into grids;threat vector of every gird is computered using radar detection probability with this proposed method.Then threat vectors to synthesize threat value are quantized.Finally,it adopts sparse-constrained ant colony algorithm to perform optimization of route planning.Simulation results show that the proposed method can obtain the optimized safe route,and cost less time compared with the traditional ant colony methods.
作者
康鹰
杨清山
冯清贤
KANG Ying;YANG Qing-shan;FENG Qing-xian(Science and Technology on Electronic Information Control Laboratory, Chengdu 610036, China)
出处
《电子信息对抗技术》
2018年第6期67-70,共4页
Electronic Information Warfare Technology
关键词
威胁向量
向量量化
稀疏约束
蚁群算法
threat vector
vector quantization
sparse constraint
ant colony algorithm
