高超声速飞行器在空天对抗中具有重要的战略价值，但日益发展的拦截技术和复杂的对抗环境干扰给飞行器规避策略设计带来巨大挑战。针对由传感器测量引入的相对距离、纵向视线角及侧向视线角三类测量误差下的高超声速飞行器追逃博弈问题，本文提出了一种双层抗干扰博弈规避控制架构。首先，根据攻防双方的运动方程，构建相对运动学模型和零和微分博弈模型，并对上述测量误差进行建模与表征。其次，在控制层设计基于非线性自适应观测器的抗干扰控制算法，补偿测量误差对系统的影响。接着，在博弈决策层制定追逃飞行器的性能指标函数，通过求解相关的Hamilton-Jacobi-Isaacs (HJI)方程推导出最优规避策略，并采用自适应动态规划技术，利用评价神经网络来近似该最优策略。最后，通过多场景数值仿真与蒙特卡洛仿真验证了所提方法的有效性与鲁棒性，分析了规避效果对三类测量误差的灵敏度，结果表明该方法能有效提升高超声速飞行器在测量误差下的规避性能。

Hypersonic vehicles hold significant strategic value in aerospace confrontation, yet the advancement of interception technologies and disturbances present in adversarial environments pose substantial challenges to the design of evasion strategies. This paper addresses the pursuit-evasion game problem of hypersonic vehicles under three types of sensor-induced measurement errors—relative distance, longitudinal line-of-sight angle, and lateral line-of-sight angle—by proposing a dual-layer anti-disturbance game-theoretic evasion control framework. First, based on the motion equations of the pursuer and evader, a relative kinematic model and a zero-sum differential game model are constructed. Measurement errors in the interceptor’s relative distance, longitudinal line-of-sight angle, and lateral line-of-sight angle are modeled and characterized. Second, at the control layer, an anti-disturbance control algorithm based on a nonlinear adaptive observer is designed to compensate for the impact of measurement errors on the system. At the game decision layer, a performance index function is formulated for the pursuing and evading vehicles. The optimal evasion strategy is derived by solving the corresponding Hamilton-Jacobi-Isaacs (HJI) equation, and adaptive dynamic programming techniques are employed, utilizing a critic neural network to approximate this optimal strategy. Finally, multi-scenario numerical simulations and Monte Carlo simulations are conducted to validate the effectiveness and robustness of the proposed method, and the sensitivity of the evasion performance to the three types of measurement errors is analyzed. The results show that the proposed method can significantly improve the evasion performance of hypersonic vehicles in the presence of measurement errors.