Parameter-Optimized Pursuit Strategy for Orbital Games with Incomplete Information
Pengxuan Liu, Bin Yang, Shuang Li, Ming Xin · Journal of Guidance Control and Dynamics · 2025
Designing efficient pursuit strategies is crucial for increasing the success rate of orbital pursuit missions. Different from a complete information game, a pursuer needs to plan effective pursuit strategies by estimating the evader’s trajectory and considering its dynamic characteristics in orbital games with incomplete information. A novel control strategy using the parameter-optimized method is developed to address the orbital pursuit problem with incomplete information. First, this paper establishes a new extended system state containing parameters that characterize the evasion strategy. The unscented Kalman filter is employed to estimate the evader’s control weighting matrices represented by these parameters. Second, leveraging the trajectory according to the evader’s strategy, a parameter-optimized control method based on the receding horizon framework is introduced to design a pursuit strategy. The method comprehensively considers maneuvering capacity and mission requirements. In each interval, a parameter-optimized method aided by the Light Spectrum Optimizer enables the pursuer to approach the evader more quickly when the maneuvering capacity is adequate. Finally, simulation results validate the effectiveness of the algorithm in estimating the evader’s strategy information and enhancing pursuit efficiency.