To address the reentry trajectory planning problem for hypersonic vehicles with spherical No-Fly Zone （NFZ） constraints， this paper proposes a Sequential Convex Programming （SCP） method based on dynamic objective reconstruction and a hybrid step-size control strategy， enabling proactive NFZ separation assurance. First， a potential function is introduced to model the spherical NFZs as soft constraints， transforming the reentry trajectory planning problem into a sequence of convex subproblems with coupled soft and hard constraints. Second， to mitigate numerical overflow issues caused by the potential function and reduce sensitivity to initial guesses， a two-phase “feasibility-optimality” dynamic decoupling framework is developed. The first phase focuses on computing a feasible solution to generate a high-quality initial trajectory for subsequent optimization， while the second phase dynamically reconstructs the optimization objective using the soft-constraint potential function to maximize the standoff distance from NFZs without significantly compromising primary performance objectives. Furthermore， a hybrid step-size control strategy is designed by integrating the trust-region method with the line-search algorithm， effectively exploiting descent information from rejected steps and improving computational efficiency. Numerical simulations demonstrate that the proposed algorithm guarantees a sufficient safety margin from spherical NFZs. Compared with the conventional trust-region convex optimization method， the proposed method improves computational speed by a 95%， and reduces terminal altitude and velocity errors by factors of 19 and 6， respectively. Compared to the Gauss pseudospectral method， the proposed approach achieves a threefold increase in computational speed while maintaining comparable terminal altitude and velocity accuracy， highlighting its promising potential for practical applications.