The Research and Development group at Lockheed Martin Canada, in collaboration with the Defence Research Establishment Valcartier, has undertaken a research project in order to capture and analyze the real-time and functional requirements of a next generation Command and Control System (CCS) for the Canadian Patrol Frigates, integrating Multi- Sensor Data Fusion (MSDF), Situation and Threat Assessment (STA) and Resource Management (RM). One important aspect of the project is to define how the use of Artificial Intelligence may optimize the performance of an integrated, real-time MSDF/STA/RM system. A closed-loop simulation environment is being developed to facilitate the evaluation of MSDF/STA/RM concepts, algorithms and architectures. This environment comprises (1) a scenario generator, (2) complex sensor, hardkill and softkill weapon models, (3) a real-time monitoring tool, (4) a distributed Knowledge-Base System (KBS) shell. The latter is being completely redesigned and implemented in-house since no commercial KBS shell could adequately satisfy all the project requirements. The closed- loop capability of the simulation environment, together with its `simulated real-time' capability, allows the interaction between the MSDF/STA/RM system and the environment targets during the execution of a scenario. This capability is essential to measure the performance of many STA and RM functionalities. Some benchmark scenarios have been selected to demonstrate quantitatively the capabilities of the selected MSDF/STA/RM algorithms. The paper describes the simulation environment and discusses the MSDF/STA/RM functionalities currently implemented and their performance as an automatic CCS.