Abstract: 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.

Key words: hypersonic vehicle, pursuit-evasion game, anti-disturbance control, zero-sum differential game, adaptive dynamic programming