This work addresses coverage formation control for the Multi-Rover System (MRS) in extraplanetary environments such as Mars or the Moon, where Global Navigation Satellite System (GNSS) signals are unavailable and uncertain self-localization significantly degrades coverage performance. Existing coverage strategies predominantly assume perfect localization, which is unrealistic for GNSS-denied planetary surfaces. This paper presents a novel multi-rover coverage formation control algorithm that combines guaranteed Voronoi partitioning with belief space planning. The core contributions are (i) a guaranteed Voronoi partitioning framework that provides deterministic bounds on true coverage cells under localization uncertainty; (ii) a dual-layer optimization architecture integrating Extended Kalman Filter-based self-localization with centroid-error minimization; and (iii) a belief space planning approach that predicts system state evolution and infers optimal control inputs over a receding horizon. Simulation results under multiple density distributions and rover configurations demonstrate faster convergence and lower coverage cost compared to conventional Lloyd-based methods. By extending existing coverage strategies, our approach supports rapid and adaptive deployment of multi-rover networks in GNSS-limited environments, providing a promising solution for large-scale planetary exploration.