基于粒子群算法的卫星任务地面站资源调度方法

A resource scheduling method for satellite mission ground station based on particle swarm optimization algorithm

针对卫星数传、测控任务的地面站资源调度问题,提出一种结合启发式方法的粒子群改进算法,对卫星的数传、测控任务进行一体化调度。首先分析卫星任务及地面站资源的约束条件,建立基于启发式规则的约束满足模型,筛选出较优的初始种群,然后设计一种结合启发式规则的粒子群算法求解。仿真对比实验表明,相对于常规调度算法(如遗传算法),粒子群算法具有较好的寻优能力和收敛速度;相对于传统粒子群算法,结合启发式方法的粒子群改进算法具有更好的寻优能力、收敛速度和稳定性。

In view of the problem of ground station resource scheduling for satellite data transmission and telemetry,tracing and control(TT&C)tasks,this paper proposes a modified particle swarm optimization(PSO)algorithm combined with heuristic methods to carry out integrated scheduling of satellite data transmission and TT&C tasks.Firstly,the constraints of satellite missions and ground station resources are analyzed,the constraint satisfaction model based on heuristic rules is established,and the superior initial population is filtered out.And then a modified PSO algorithm combining heuristic rules is designed to solve the resource scheduling problem.The simulation and comparison experiments show that the PSO algorithm has better ability to find excellence and convergence speed than traditional scheduling algorithm(such as genetic algorithm),and that the modified PSO algorithm has better ability to find excellence,convergence speed and stability than the traditional PSO algorithm.