Method for Low Earth Orbit Satellite Communication Task Planning Based on Optimal Neighborhood Search PSO Algorithm
Aiming at the mission planning problem in low earth orbit satellite communication,a mission planning method based on the optimal neighborhood search Particle Swarm Optimization(PSO)algorithm is proposed.First,the optimal nearest neighbor search is introduced to promote local search through the difference value between optimal particles.The second step is to design the optimization method of inertia weight,social and self-learning factors.Ultimately,this method can effectively solve the combined optimization problem of multi-transponders and multi-tasks in low earth orbit satellite communication constellations,and cope with the discrete time period problem caused by low earth orbit satellite transit time constraints and link switching.And this algorithm has a strong ability to explore the global optimum in the early stage and quickly converge in the later stage.Experimental verification results show that the method pro-posed can effectively increase the Average Occupancy Percentage(AOP)of satellites under multi-constraint conditions of low-orbit sat-ellites,effectively reduce the number of iterations of algorithm convergence,and significantly reduce the running time overhead.
task planningPSOheuristic algorithmoptimal neighborhood searchlow earth orbit satellite communication
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