Collaborative task planning model and algorithm of network imaging satellites

As a kind of important earth observation satellites, network imaging satellites can improve the ability of processing complicate tasks, however, the process of solving complicate tasks is an optimization problem with multi-time windows, multitask, and multi-resource constrains, especially when processing collaborative tasks. This paper focuses on collaborative task scheduling problems, and three respects of work are done: firstly, networking collaborative task planning model is built, which overall considers common task and complicate task, and integrate the collaborative mechanism; secondly, an improved genetic algorithm is proposed, which introduces variable neighbor search strategy by combining immune colonel selection, so as to improve convergence performance and robustness of discrete combination optimization problem; finally, through STK provides the basic simulation data, experiments in our HLA based simulation system verify the effectiveness of above model and algorithm.