Long-range guided rockets have a long range and high power, and have been widely integrated into modern weapon and equipment systems, becoming one of the weapon systems that countries are competing to develop. Long-range guided rockets are complex systems composed of multiple subsystems, and multidisciplinary, nonlinear, and time-consuming characterize their design process. To improve the design performance of long-range guided rockets, a multidisciplinary parametric model of long-range guided rockets is first established to achieve high-precision performance simulation of guided rockets. Secondly, a sequence approximation optimization method based on an improved augmented radial basis function is proposed, which enhances the generalization ability of the augmented radial basis function model through anisotropic techniques. Recursive evolution experimental design and fast cross-validation are used to improve the efficiency of approximation modeling, and an imprecise search strategy is applied for sequence sampling. The effectiveness of the proposed optimization method is verified through numerical examples. Finally, a sequence approximate optimization design of the long-range guided rocket is carried out, and the maximum range increased by 16.7% compared to before optimization while satisfying design constraints.