Simulation Research Based on Spacecraft Collaborative Combat Mode
A method for non cooperative target tracking and escape game in satellite clusters in orbital space is proposed.This method solves the problem of complex dynamic models and difficult coordination between satellites.Based on the multi-agent deep reinforcement learning algorithm,a dynamic model of the satellite cluster game scenario was first constructed,and the optimal strategy for each satellite was trained using the multi-agent deep deterministic policy gradient algorithm(MADDPG),while considering the minimum fuel consumption and shortest time.Then,distributed execution was used to achieve the chase and escape game.The results indicate that when the performance of chasing and escaping satellites is the same,the distance between them remains constant,reaching the Nash equilibrium point.When the number and performance of escaping spacecraft and chasing satellites are different,chasing satellites can learn optimal strategies and successfully capture escaping spacecraft.This method can provide a new approach and approach for solving the game problem of satellite clusters in orbital space.
pursuit and evasion modelnon cooperative complete information gameNash equilibrium
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