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Lifetime maximization is a key challenge in the design of sensor-network-based tracking applications. In this paper, formation of optimal coalitions of nodes is investigated for data acquisition in bearings-only target localization such that the average sleep times allocated to the nodes are maximized. Cooperative game theory is utilized as a tool to devise a distributed dynamic coalition formation algorithm in which nodes autonomously decide which coalition to join, while maximizing their feasible sleep times. If each node follows the proposed algorithm, the average sleep time for the entire network eventually converges to its maximum feasible value conditional on the pre-defined localization accuracy. This algorithm can also be employed in tracking slow moving targets.