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Localization and synchronization are two important issues in communication systems and wireless sensor networks. These two problems are addressed in many applications, and share many aspects in common. However, these two problems are traditionally treated separately. In this paper, we present a unified framework to jointly solve these two problems at the same time. The maximum likelihood joint estimation of location and timing is firstly derived. Then, a more computationally efficient two-stage least square method is proposed. The Cramer-Rao lower bound for the joint localization and time synchronization is also derived. Simulation results show that the performances of the maximum likelihood and two-stage least square estimators can both achieve the Cramer-Rao lower bound.