基于粒子群的无人机蜂群网络拓扑快速构建方法

Fast Construction Method of Distributed Topology for UAV Swarm Network

高稳定性的网络拓扑是无人机蜂群系统分布式联合感知、分布式信息交互与分布式协同控制等集群功能的重要保障。在三维动态应用场景中,快速稳定的网络拓扑构建对于蜂群系统的可靠应用具有重要意义,而当前的拓扑构建方法在此方面研究并不充分。提出了一种基于粒子群优化算法(PSO)的无人机蜂群分布式拓扑快速构建方法,在满足蜂群网络特定的端到端通信时延性能要求下,最大化网络拓扑的维持时间。为实现分布式拓扑构建方法的快速收敛,根据蜂群节点的静态特性和动态趋势进行初值设计,同时基于特征相似度函数优化更新方向与步长。仿真结果表明,在典型应用场景和系统配置下,该方法具有高拓扑稳定性。在蜂群规模为100节点时,传统PSO策略需要平均5.5次迭代才能获得最优解,而该算法在获得相同端到端时延和网络吞吐性能的同时,平均只需2次迭代即可收敛到全局最优解。

A highly stable network topology is an important guarantee for the collaborative functions of the Unmanned Aerial Vehicle(UAV)swarm system,including the distributed joint sensing,distributed information interaction and distributed cooperative control.In 3D dynamic application scenarios,fast and stable network topology construction is crucial for reliable applications of swarm systems,and current topology construction methods are not sufficiently studied in this aspect.In this paper,a fast distributed topology construction method for UAV swarm system is proposed,the method is based on a Particle Swarm Optimization(PSO)algorithm that maximizes the duration of network topology under the specific end-to-end communication delay performance requirement.To achieve fast convergence of the distributed topology construction method,the initial values are designed according to the static characteristics and dynamic trends of the swarm nodes,while the update direction and step size are optimized based on the feature similarity function.The simulation results show that the proposed method of topology construction has high stability under typical application scenarios and system configurations.With 100 nodes,the traditional PSO strategy requires an average of 5.5 iterations to obtain the optimal solution,while the proposed algorithm converges to the global optimal solution in an average of 2 iterations obtaining the same end-to-end delay and network throughput performance.