基于狼群优化的卫星集群对空间目标围捕方法

An essential part of space orbit competition research is the way the satellites swarm together to generate a round-up situation for space targets. The round-up situation can effectively support the satellite swarm to implement detection and perception with all-around and real-time performance and multi-angle pursuit-evasion game for space targets. Most of the existing research on the problem of space target pursuit-evasion was based on the differential game theory to establish the game model to solve one pursuit and one escape problem. It is a research difficulty for satellite swarms to cooperate and realize round-up in the form of groups. Aiming at the problem of rounding up a space target with a satellite swarm, a method based on a wolf pack optimization algorithm is proposed. Discrete the total duration of the round-up task into multiple decision-making cycles, and design a fitness function that comprehensively considers the position distribution of the satellite swarm, the round-up situation, the fuel consumption and safety collision avoidance. Control the satellite swarm to close to the target satellite and to distribute approximately evenly on the sphere with the target as the center via co-optimizing the thrust vector of satellite swarm in the decision-making cycle. The outcomes of the simulation demonstrate that the approach is capable of obtaining the satellite swarm's maneuvering strategy to swiftly round up the space target, create a round-up scenario, and efficiently support the space orbit competition task.