In this paper, we consider the general problem of dynamic assignment of sensors to local fusion centers (LFCs) in a distributed tracking framework. As a result of recent technological advances, a large number of sensors can be deployed and used for tracking purposes. However, only a certain of number of sensors can be used by each local fusion center due to physical limitations. In addition, the number of available frequency channels is also limited. We can expect that the transmission power of the future sensors will be software controllable within certain lower and upper limits. Thus, the frequency reusability and the sensor reachability can be improved. Then, the problem is to select the sensor subsets that should be used by each LFC and to find their transmission frequencies and powers, in order to maximize the tracking accuracies as well as to minimize the total power consumption. This is an NP-hard multi-objective mixed-integer optimization problem. In the literature, sensors are clustered based on target or geographic location, and then sensor subsets are selected from those clusters. However, if the total number of LFCs is fixed and the total number of targets varies or a sensor can detect multiple targets, target based clustering is not desirable. Similarly, if targets occupy a small part of the surveillance region, location based clustering is also not optimal. In addition, the frequency channel limitation and the advantage of the variable transmitting power are not discussed well in the literature. In this paper, we give the mathematical formulation of the above problem. Then, we present an algorithm to find a near optimal solution to the above problem in real time. Simulation results illustrating the performance of the sensor array manager are also presented.