基于遗传算法的太阳同步轨道组网访问序列优化

Access sequence optimization of genetic algorithm based solar synchronous orbit networking

针对考虑回归周期、重访周期及地面站接收数据冲突等多约束条件下太阳同步回归轨道多星组网问题,开展了基于遗传算法的组网优化研究。通过分析太阳同步回归轨道运动特性与星下点的关系,构造了回归周期内轨道的访问序列,建立了卫星半长轴、相位差与太阳同步回归轨道的关系;结合组网卫星有效载荷指标参数,分析了回归周期、重访周期与访问序列的关系及极值;将组网卫星的访问序列作为优化参数,采用二进制编码方式建立综合适应度函数;设计了遗传算子并通过种群繁殖得到优化结果。仿真结果表明,该方法能够快速设计出满足约束条件的组网优化策略。

For the problem of solar synchronous return orbit multi satellite networking with the consideration of multiple constraints, such as return period, revisit period and data conflict of ground station, the optimization research based on genetic algorithm is carried out. Based on the analysis of the relationship between the motion characteristics of the sun synchronous return orbit and the point of the sun, the access sequence of the orbit in the return period is constructed, and the relationship between the semi major axis of the satellite, the phase difference and the sun synchronous return orbit is established. Combined with the parameters of the satellite payload index, the relationship and extremes between the return period, revisit period and access sequence are analyzed. Taking the access sequence of the networking satellites as the optimization parameter, the binary coding method is used to establish the comprehensive fitness function, and the genetic operator is designed to obtain the optimization result through population propagation. Simulation results show that the method can quickly design the network optimization strategy that meets the constraints.