基于遴选蜜獾的结点缩减无人机渗透路径规划
Node Reduction UAV Penetration Path Planning Based on Honey Badger Selection
李勇 1白梅娟 1付高阳 2周敏敏 1李昊瞳 1侯帅1
作者信息
- 1. 河北工程大学信息与电气工程学院,河北邯郸 056038
- 2. 邯郸市生态环境局环境保护督查中心,河北邯郸 056004
- 折叠
摘要
无人机渗透作战指隐藏航迹,穿越敌人密集区域向敌人后方运动,是一种重要的作战样式.为了解决无人机在城市场景下的渗透路径规划问题,提出了一种基于遴选策略的蜜獾算法(Select Excellent Individuals Honey Badger Algorithm,SEI-HBA),它能够在隐蔽度模型下规划无人机的渗透路径.首先,提出一种根据划分低隐蔽区域减少区域内路径数量的结点缩减模型;其次,提出遴选策略蜜獾算法,将蜜獾种群中满足阈值的个体遴选出作为优秀个体,引导种群中剩余个体求解方向;最后,通过划分结点类型,考虑敌方有效视野、建筑物与敌方的位置分布构建无人机城市渗透隐蔽度计算模型.实验证明,遴选蜜獾算法结合渗透模型的无人机路径规划相比于传统只考虑路程最短的无人机路径规划,取得了良好的实验效果,为渗透背景下的路径规划提供了新的方法和思路.
Abstract
UAV infiltration combat refers to hiding the trajectory and moving through the dense enemy area to the rear of the enemy,which is an important combat style. In order to solve the problem of UAV infiltration path planning in urban scenarios,a selection strategy-based Honey Badger Algorithm (SEI-HBA) is proposed,which is capable of planning UAV infiltration paths under the concealment model. Firstly,a node reduction model is proposed to reduce the number of paths in the region according to the division of low concealment region;secondly,the selection strategy Honey Badger Algorithm is proposed to select the individuals that satisfy the threshold value in the honey badger population as the excellent individuals,and guide the direction of the remaining individuals in the population to find the solution;finally,the UAV urban infiltration concealment computation model is constructed by dividing the types of nodes,and taking into consideration of the enemy's effective field of view,and the distribution of the positions of buildings and the enemy. model. The experiment proves that the UAV path planning with the honey badger algorithm combined with the infiltration model proposed in this paper achieves good experimental results compared with the traditional UAV path planning that only considers the shortest distance,and provides a new method and idea for the path planning in the context of infiltration.
关键词
结点缩减/遴选策略/蜜獾算法/隐蔽度模型Key words
node reduction/selection strategy/honey badger algorithm/hiddenness modeling引用本文复制引用
基金项目
河北省自然科学基金面上项目(F2021402009)
河北省自然科学基金面上项目(A2020402013)
出版年
2024
NETL
NSTL
万方数据