Satellite Constellation Design for Multi-objective Coverage Based on Double-layer Optimization
Addressing the issue of continuous coverage of dispersed ground targets by communication satellites,a well-planned constellation configuration of satellites can minimize constellation deployment costs while guaranteeing communication coverage constraints.In traditional constellation design schemes,the existence of numerous scattered ground targets frequently results in suboptimal outcomes.To alleviate this situation,a two-level optimization approach based on"inner layer+outer layer"for the multi-objective coverage satellite constellation optimization design is proposed.Firstly,in the inner layer,a clustering algorithm is utilized to cluster target locations rationally,and a multi-objective particle swarm algorithm is adopted to optimize the trajectories assigned to each group of target locations,with the aim of maximizing the coverage of ground targets by satellites in the early stage of constellation design.Subsequently,in the outer layer,a 0-1 programming algorithm is implemented to generate the optimal constellation configuration code with the minimization of the number of satellites as the optimization criterion for designing a satellite constellation configuration that achieves continuous communication coverage throughout the day.Simulation results show that this optimization scheme,under the prerequisite of fulfilling the requirement for single-layer continuous coverage,can enhance the coverage capability of individual satellites for target locations within the constellation,reduce the number of satellites,and thereby decrease the constellation deployment costs.
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