Genetic-evolutionary bi-level mission planning algorithm for multi-satellite cooperative observation
Multi-satellite cooperative mission planning method is a key node in the space-based satellite system architecture.Firstly,the multi-satellite cooperative for Earth observation mission is analyzed and a multi-satellite cooperative mission planning model is established,including satellite orbit parameters,constraint conditions,and target points to be observed.Then,a genetic-evolutionary bi-level solution architecture is designed,which decomposes the multi-satellite mission planning problem into a top multi-satellite mission assignment problem and a bottom single-satellite mission scheduling problem.The upper level uses the guided multi-population genetic algorithm(MPGA)to integrate the heuristic results into the task allocation algorithm,and the lower level uses the improved genetic algorithm to solve the single-satellite task scheduling problem.Finally,aiming at the applicability problem,two groups of objectives are set randomly and uniformly distributed,and experiments are designed with different numbers of satellites to prove the effectiveness of the genetic-evolutionary bi-level solution framework.
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