Guided Collaborative Task Scheduling Model And Algorithm Of Reconnaissance Satellite

In recent years, the quantity and the type of satellites is increasing with the application of satellites is rapid developing. At the same time, observation require ment of satellite from users is also become more and more complex and diverse, the complexity resulting from the users’ requirement that the urgency of the time, the extensity of the coverage, and the integrity of the imaging type, and so on. Now a single satellite is not able to meet the increasing demand for user, different types of satellites complete observation task in collaboration with each other has become very important. However, most of the existing satellite task scheduling model and algorithm mainly targets the single or the same satellites, it is faced with the problem that the scheduling is ineffective, observation is difficult to meet the demand of users, and the resource utilization is low. Exactly the guided collaborative task scheduling as an important collaborative mode can solve the problem well, so this paper focuses on studying the guided collaborative task scheduling, the specific work as follows:(1) According to the characteristics of the guided collaborative task scheduling, elaborates the specific process of guided collaborative task scheduling, and clears the roles and responsibilities of satel ites in the process of observation collaboratively.(2) Considering the properties of satellites itself, the requirement of users, and the characteristics of guided collaborative observation, summarized the typical guided cooperative mode and to be represented with symbol.(3) Under the condition of considering basic constraint, different satellites’ constraint, and guided collaborative constraint, a constraint satisfaction model for the guided collaborative task scheduling is established.(4) Introducing the risk factors to the optimization goal. The risk factors include the external environment risk threat, the adjustment of task preperty, and the changes of satel ite availability. In this way, an optimization goal considering risk factor is designed.(5) Designing a guided collaborative solution scheme. To the guided satellites, adopt a variable neighborhood searching algorithm based a double immune network by combining immune clonal selection algorithm and immune genetic algorithm; To the observed satellites, on the basis of the guide satellites planning adopt an algorithm based on heuristic rules; finally finishing the algorithm of the whole guided collaborative task scheduling.