Data Distribution Management (DDM) is one of the services defined by the DoD High Level Architecture. DDM is necessary to provide efficient, scalable mechanisms for distributing state updates and interaction information in large scale distributed simulations. In this paper, we describe data distribution management mechanisms (also known as filtering) used for real time training simulations. We propose a new DDM approach to multicast group allocation, which we refer to as a Dynamic Grid-Based Allocation. Our scheme is based on a combination of a Fixed Grid-Based method, known for its low overhead and ease of implementation, and a Sender-Based strategy, which uses fewer multicast groups than the Fixed Grid-Based method. We describe our DDM algorithm, its implementation, and report on the performance results that we have obtained using the RTI-Kit framework. These results include the outcome of experiments comparing our approach to the Fixed Grid-Based method, and they show that our scheme is scalable and significantly reduces the message overhead of previous Grid-Based allocation schemes.