Emergency Mission Planning of Sky Survey Based on Multi-Objective Particle Swarm Algorithm

The China Sky Survey Space Telescope (CSST) is a large-scale space astronomy project planned and constructed by China, which is of great significance in promoting the development of astronomy and many other fields. Sky survey is its main task, and it has a large number of observations, a wide observ...

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Vydané v:2024 5th International Conference on Electronic Communication and Artificial Intelligence (ICECAI) s. 24 - 31
Hlavní autori: Jia, Rongsheng, Wang, Hongfei
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 31.05.2024
Predmet:
Accuracy
Analytical models
Heuristic algorithms
mission planning
particle swarm algorithm
Particle swarm optimization
Planning
sky survey
Surveys
Telescopes
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Shrnutí:The China Sky Survey Space Telescope (CSST) is a large-scale space astronomy project planned and constructed by China, which is of great significance in promoting the development of astronomy and many other fields. Sky survey is its main task, and it has a large number of observations, a wide observation range, a long mission cycle and is subject to complex constraints during its in-orbit operation. This paper combines the actual needs of engineering, analyzes the scientific objectives and mission constraints of the dynamic planning problem of the roving mission, establishes a dynamic mission planning model, and adopts a multi-objective particle swarm algorithm to solve the emergency mission planning problem. The algorithm is able to incorporate the emergency mission into the observation plan. Simulation experiments were conducted according to the actual scenarios, and different sizes of emergency mission data sets were set up for experiments and compared with NSGA-II and NSGA-III algorithms. The results show that the multi-objective particle swarm algorithm is higher than the other two algorithms in terms of solution accuracy and time efficiency.
DOI:10.1109/ICECAI62591.2024.10674846