The statistical characteristics of noise in integrated micro inertial measurement unit/global navigation satellite systems（MIMU/GNSS）are difficult to obtain in complex environments，and simplified probabilistic assumptions may lead to performance degradation or even failure of the navigation system. To enhance the adaptability of navigation systems in complex environments while maintaining navigation accuracy and real-time performance，a rapid fusion algorithm is proposed for MIMU/GNSS based on the assumption of unknown but bounded noise. Building upon the input-to-state stable ellipsoidal bounding filter，this algorithm optimizes bounding ellipsoid parameters through relaxation of the optimization objective，thereby avoiding solutions to nonlinear equations and reducing computational complexity. The rapid algorithm was applied to MIMU/GNSS-integrated navigation experiments. The experimental results demonstrated that the proposed rapid fusion algorithm effectively improves system navigation accuracy while ensuring real-time navigation performance.