Controlled mobility of nodes in mobile sensor networks allows for autonomous deployment and further optimization of network coverage after initial deployment. When sensor nodes have non-identical sensing ranges, more sophisticated optimization techniques should be used to solve for distributed relocation algorithms that maximize coverage. In this work, novel geometric methods are presented to address this problem. The proposed iterative algorithms use the available local information to judiciously relocate mobile sensors to new positions. This process leads to a continuous reduction in the size of coverage gaps throughout the field. Simulation results demonstrate the performance of the proposed algorithms in improving network coverage.