In widely distributed multiple radar systems, employing larger numbers of transmit and receive antennas supports better target parameter estimation. Increased dimensions results in higher communication needs, synchronization overhead, and processing complexity. In our previous studies, resource-aware operational schemes have been introduced for a given localization estimation mean-square error (MSE) threshold requirement. Power allocation scheme that minimizes the total transmitted power for a given MSE goal has been derived. As most of the transmitted power was allocated to a few of the available transmit antennas, a subset selection scheme has been proposed to identifying a minimal set of transmit and receive antennas that offer the required accuracy performance. The study indicates that some transmit and receive antenna pairs contribute more than others to the localization performance. Based on this, a different approach to resource-aware operation is proposed in this paper. The objective is to identify an antenna subset that offers an optimal tradeoff between performance loss in term of localization MSE and the active subset size. By setting an acceptable loss threshold, relative to the best performances achievable with all antennas active, joint optimization of subset size and power allocation is performed to maximize the trade-off gains. A mixed optimization problem is defined, based on the Cramer-Rao bound (CRB), and fast approximation algorithm is proposed, maximizing the trace of the Fisher information matrix (FIM) while minimizing the number of active antennas. The closed-form expression of the CRB offers additional understanding of the relation between the geometric layout of the transmit and the receive antennas with respect to the target and their relative contribution to the performance.