Review on Optimization of Simulation Modeling Strategies for Spacecraft Orbit Avoidance

doi:10.16182/j.issn1004731x.joss.25-0277

Abstract

Abstract:

The number of on-orbit spacecraft increases exponentially; the space environment becomes more complex, and the collision risk of on-orbit spacecraft increases significantly. On-orbit safety is thus severely threatened, posing higher requirements for orbit avoidance methods. The costs and risks of space activities are extremely high, making simulation an effective method to solve complex problems of orbit avoidance. The modeling, solution, and simulation methods for the two core issues of spacecraft orbit avoidance, "collision avoidance" and "pursuit-evasion games", were systematically reviewed, and the existing shortcomings were analyzed. The applications of technologies such as deep reinforcement learning in promoting orbit avoidance modeling and simulation were introduced.

Key words: spacecraft, orbit avoidance, collision avoidance, pursuit-evasion game, reinforcement learning

CLC Number:

Li Guozheng, Wang Rui, Fan Shichao, Cai Xintong, Zhai Xinyue. Review on Optimization of Simulation Modeling Strategies for Spacecraft Orbit Avoidance[J]. Journal of System Simulation, 2026, 38(4): 855-868.

Figures/Tables 6

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