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Automatic trajectory planning for low-thrust active removal mission in Low-Earth Orbit

机译:低地球轨道低推力主动清除任务的自动轨迹规划

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摘要

In this paper two strategies are proposed to de-orbit up to 10 non-cooperative objects per year from the region within 800 and 1400 km altitude in Low Earth Orbit (LEO). The underlying idea is to use a single servicing spacecraft to de-orbit several objects applying two different approaches. The first strategy is analogous to the Traveling Salesman Problem: the servicing spacecraft rendezvous with multiple objects in order to physically attach a de-orbiting kit that reduces the perigee of the orbit. The second strategy is analogous to the Vehicle Routing Problem: the servicing spacecraft rendezvous and docks with an object, spirals it down to a lower altitude orbit, undocks, and then spirals up to the next target. In order to maximise the number of de-orbited objects with minimum propellant consumption, an optimal sequence of targets is identified using a bio-inspired incremental automatic planning and scheduling discrete optimisation algorithm. The optimisation of the resulting sequence is realised using a direct transcription method based on an asymptotic analytical solution of the perturbed Keplerian motion. The analytical model takes into account the perturbations deriving from the $J_2$ gravitational effect and the atmospheric drag.
机译:在本文中,提出了两种策略,以每年从低地球轨道(LEO)的800和1400 km高度区域对多达10个非合作物体进行离轨。其基本思想是使用单个维修航天器使用两种不同方法使几个物体脱离轨道。第一种策略类似于“旅行推销员问题”:为多个物体会合的维修航天器,以物理方式安装可减小轨道近地点的去轨道套件。第二种策略类似于“车辆路线问题”:维修航天器会合并与一个物体对接,然后将其螺旋下降到较低的高度轨道,解开,然后螺旋上升到下一个目标。为了以最小的推进剂消耗最大化离轨物体的数量,使用生物启发式增量自动规划和调度离散优化算法来确定最佳目标序列。使用直接转录方法,基于扰动的开普勒运动的渐近解析解,可以实现对所得序列的优化。该分析模型考虑了由$ J_2 $引力效应和大气阻力引起的扰动。

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