Abstract Onboard mission planning for agile satellite using modified mixed-integer linear programming
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Onboard mission planning for agile satellite using modified mixed-integer linear programming

机译：使用改进的混合整数线性规划进行敏捷卫星的机载任务计划

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AbstractThis paper investigates a new Agile Earth Observation Satellite (AEOS) mission planning algorithm. This new developed algorithm is based on Modified Mixed-Integer Linear Programming (MILP) approach, which takes the minimum slew angle and highest priority criterion. The key point of the paper lies in that the planning process is treated as a Dynamical Combinatorial Optimization (DCO) problem due to the time-varying constraint and the requirement of the problem. The design of the new algorithm is also to meet the real-time requirement of onboard mission planning. The mathematical formulation of the problem is modified to satisfy the demand of the LP solver, and a newly developed dynamic database is used to simulate the constantly changing satellite-target relative position with limited observation windows. The new mission planning model is solved by the LP method to test its reliability. Another solution with Generic Algorithm (GA) is also given to check the result. The calculation time of these two methods is compared to show that the LP approach has a better compatibility with the onboard mission planning requirement.
机译： 摘要 本文研究了一种新的敏捷地球观测卫星（AEOS）任务计划算法。该新开发的算法基于改进的混合整数线性规划（MILP）方法，该方法采用最小的摆角和最高的优先级标准。本文的重点在于由于时变约束和问题的要求，将规划过程视为动态组合优化（DCO）问题。新算法的设计还可以满足机载任务计划的实时要求。修改了问题的数学公式，以满足LP解算器的需求，并使用新开发的动态数据库来模拟观察窗口有限的，不断变化的卫星目标相对位置。通过LP方法解决了新的任务计划模型，以测试其可靠性。还给出了使用通用算法（GA）的另一种解决方案来检查结果。比较了这两种方法的计算时间，表明LP方法与机载任务计划要求具有更好的兼容性。

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