This paper addresses the optimal longitudinal tracking control problem for Hypersonic Vehicles (HVs) under input saturation constraint. To handle its inherent nonlinearities and control limitations, an Adaptive Dynamic Programming (ADP) based approach is proposed. A novel performance index function is proposed, which explicitly accounts for input saturation within the optimization framework. Leveraging this function, the discrete-time Bellman optimality equation is derived, and an input saturation ADP (ISADP) algorithm employing value iteration is developed, whose convergence to the optimal control policy is proven. An Actor-Critic neural network structure is utilized for practical implementation. A simulation validates the effectiveness of the proposed strategy in achieving optimal tracking performance in the presence of input saturation.