Within the domain of Intelligent Group Systems (IGSs), this paper develops a resource-aware multitarget Constant False Alarm Rate (CFAR) detection framework for multisite MIMO radar systems. It underscores the necessity of managing finite transmit and receive antennas and transmit power systematically to enhance detection performance. To tackle the multidimensional resource optimization challenge, we introduce a Cooperative Transmit-Receive Antenna Selection and Power Allocation (CTRSPA) strategy. It employs a perception-action cycle that incorporates uncertain external support information to optimize worst-case detection performance with multiple targets. First, we derive a closed-form expression that incorporates uncertainty for the noncoherent integration squared-law detection probability using the Neyman-Pearson criterion. Subsequently, a joint optimization model for antenna selection and power allocation in CFAR detection is formulated, incorporating practical radar resource constraints. Mathematically, this represents an NP-hard problem involving coupled continuous and Boolean variables. We propose a three-stage method—Reformulation, Node Picker, and Convex Power Allocation—that capitalizes on the independent convexity of the optimization model for each variable, ensuring a near-optimal result. Simulations confirm the approach’s effectiveness, efficiency, and timeliness, particularly for large-scale radar networks, and reveal the impact of threat levels, system layout, and detection parameters on resource allocation.