During normal operation of the on-orbit spacecraft, if some satellite in a nearby orbit suddenly breaks apart, its debris will threat the safe operation of the on-orbit spacecraft. Therefore, it is necessary to study the active spacecraft’s avoidance of the space debris group and returning to the original orbit. In this way, the safe operation of on-orbit spacecraft will be guaranteed. However, as the geometric structure of the space debris group is constantly changing, it is hard to accurately demonstrate the changing shape of the debris group, let alone determine the unreachable domain. Traditional obstacle avoidance problems involve low speed of the vehicle; so, the application of artificial potential field and particle swarm algorithms is suitable for such problems. However, these two methods are not applicable to the maneuver strategy of spacecraft with high initial velocity. Therefore, to help spacecraft avoid the space debris group, a new method is required. This paper has established a simplified model to simulate the unreachable domain of the space debris group. It has modified the artificial potential field (APF) method and particle swarm optimization algorithm, with an aim to help spacecraft avoid the space debris group and return to the original orbit. Based on the method, the paper has proposed a three-stage maneuver strategy for the spacecraft to avoid the debris. To show the effectiveness of the method, this paper has simulated an on-orbit spacecraft’s avoidance of the space debris group nearby and returning to its original orbit. Through simulation, the feasibility of the maneuver strategy for spacecraft in the geosynchronous orbit is evaluated. The simulation results show that the method proposed in this paper can effectively accomplish the task.


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    Title :

    Maneuver Strategy for Active Spacecraft to Avoid Space Debris and Return to the Original Orbit


    Contributors:
    Qun Fang (author) / Zhen Zhang (author) / Haodong Meng (author) / Xiaolong Wang (author) / Xiuwei Zhang (author)


    Publication date :

    2022




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




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