To improve the design performance of long-range guided rockets, a multidisciplinary parametric model of long-range guided rockets was first established to achieve high-precision performance simulation of guided rockets. A sequence approximation optimization method based on an improved augmented radial basis function was proposed, which enhanced the generalization ability of the augmented radial basis function model through anisotropic techniques. Recursive evolution experimental design and fast cross-validation were used to improve the efficiency of approximation modeling, and an imprecise search strategy was applied for sequence sampling. The effectiveness of the proposed optimization method was verified through numerical examples. A sequence approximate optimization design of the long-range guided rocket was carried out, and the maximum range increase by 16.7% compared to before optimization while satisfying design constraints.