在多星轨道博弈任务中，各航天器通过感知获取当前态势，依据态势变化制定博弈策略，生成期望的速度脉冲，并根据执行机构的特性生成推力器开机时间，最终产生期望的速度脉冲。上述过程可以用感知-决策-执行（ODA）一体化系统进行描述，系统的闭环时间对于多星博弈任务的成败至关重要，如何在一体化系统的时间约束下进行高效决策，是提升博弈效能的关键。本文以追踪星、逃逸星和防御星组成的三星追逃博弈场景为例，提出一种纳什均衡快速求解方法，并在此基础上开展自适应追踪策略设计，使得追踪星既能抵近逃逸星，同时也能避免被防御星抵近。首先，为了支撑纳什均衡求解，建立航天器的相对可达域解析模型；其次，以相对可达域模型为基础，提出双星追逃的纳什均衡策略的快速求解方法，并揭示三星博弈纳什均衡解的分布范围，有效降低数值寻优的计算复杂度；并且为了提升追踪星应对不同对手的追踪能力，建立参数自适应机制，动态调整优化指标参数，改变纳什均衡解的分布。最后，通过数值仿真验证本文所提纳什均衡策略的正确性以及时效性。

In the multi-satellite orbital game mission, each spacecraft obtains the current situation through observation, and then formulates maneuver strategies according to observation results and plans the working time of the thrusters based on the characteristics of the actuator to generate the desired velocity impulses. This process can be described by an integrated Observation - Decision - Actuation (ODA) system. The closed-loop time of the system is crucial to the orbital mission. Making efficient decisions under the time constraints of the integrated system is the key to improving the game efficiency. This paper focuses on the three-satellite pursuit-evasion game, which com-poses of a pursuer, an evader, and a defender. A fast-solving method for the Nash equilibrium is proposed and then an adaptive pursuing strategy is proposed such that the pursuer can track the evader while avoiding the defender. Firstly, in order to efficiently solve the Nash equilibrium under impulsive thrust, an analytical model of the relative reachable region of the spacecraft is established. Then, the fast-solving method for the Nash equilibrium of the two participants is proposed based on the reachable region and the distribution of the Nash equilibrium for the three participants is analyzed. This method can reduce the optimization range and the calculation complexity of numerical optimization. Besides, in order to improve the tracking ability of the pursuer against different opponents, a parameter-adaptive mechanism is established to dynamically adjust the optimization index parameters such that the the distribution of the Nash equilibrium can be changed accordingly. Finally, the correctness and efficiency of the Nash equilibrium strategy proposed in this paper is verified through numerical simulation.