基于紫外光隐秘通信的无人机编队分簇优化算法

Clustering Optimization Algorithm for Unmanned Aerial Vehicle Formation Based on Ultraviolet Security Communication

针对复杂战场环境下无人机(UAV)执行渗透侦察任务时对通信网络的隐秘性需求,考虑节点携带能源有限且在数据传输时能量消耗的不均衡问题,提出了一种基于紫外光通信的UAV编队分簇优化算法。首先,在建立机间无线紫外光通信链路模型和能量消耗模型的基础上,结合最优刚性图的优势,对低功耗自适应分层型协议(LEACH)算法的簇首选举和簇间通信过程进行改进。然后,引入节点剩余能量和链路可靠性的权值函数选举簇首,簇首间通过生成最优刚性图进行拓扑优化。仿真结果表明,该算法在提高簇间连通性的同时延缓了网络出现节点死亡的现象,相比LEACH算法,网络第一次出现死亡节点和出现一半死亡节点的时间分别延长了25.2%和21.4%,且兼顾了网络的连通性和能耗均衡性。

In view of the secret demand of communication network for unmanned aerial vehicle(UAV)in penetrating reconnaissance mission under the complex battlefield environment,considering the limited energy carried by nodes and the unbalanced of energy consumption during the data transmission,a clustering optimization algorithm for UAV formation based on ultraviolet communication is proposed in this paper.First,on the basis of establishing the wireless ultraviolet communication link model and energy consumption of nodes,the selection of cluster heads and inter-cluster communication process of low energy adaptive clustering hierarchy(LEACH)algorithm is improved.Then,the weight functions of node residual energy and link reliability are introduced to select cluster heads,and the topology optimization between cluster heads is carried out by generating optimally rigid graph.The simulation results show that the algorithm improves the connectivity between clusters and delays the phenomenon of node death in the network.Compared with the LEACH algorithm,the time for the first occurrence of dead nodes and half of dead nodes in the network is delayed by 25.2% and 21.4%,respectively.The connectivity and energy balance of the network are improved.