Algorithm design and system application of HY-1 satellite observation mission planning

Aiming at the observation mission planning of HY-1 satellite, a planning algorithm based on genetic strategy was proposed and implemented to solve the planning constraints and resource maximization problems in the context of practical scenario. Based on the practical planning issues of HY-1 satellite, a mathematical model was established for the mission planning constraints and optimization objectives, and the observation task constraints were innovatively divided into window constraints and combination constraints. The optimization objective function of multi -constraint task planning was designed, and the optimization problem was solved by using genetic mechanisms including crossover, mutation and population selection. Based on the practical observation demand data of HY-1 satellite, the validity and performance of the proposed algorithm were verified. The results show that this algorithm can provide observation plans that meet the constraints of satellite planning and that it gets better performance than other strategies in terms of observation time and observation demand coverage. The research results show that the genetic algorithm can realize the more complex multi -type observation mission planning constraints, and the research results can provide reference for mission planning of remote sensing satellites with similar business characteristics to HY satellites.