Review of Data Fusion Models and Architectures for Air Targets Threat Assessment in C4I System

By integrating data into multi-sensor networks, the uncertainty and ambiguity in C4I systems is reduced and in these systems, the complexity and execution time of operational computations based on the operating environment is reduced. This successful combination of data and information is accomplished by a variety of models and architectures that have been proposed for implementation in a variety of military and civilian applications. A robust and organized strategy in the operation environment is needed to facilitate the solution of the problem before performing the process of integrating the data received from the sensors. Due to differences in military and civilian applications of data fusion, it is not possible to create a single hardware and software platform for data fusion in the C4I system. In this system, due to the high volume and importance of processing and information exchange speed, the use of data fusion technology to increase the accuracy and reliability of output results due to the operational cycle of each of the data integration models and architectures, is necessary. This paper, reviews the types of different models and architectures integrated to assess the threat in the C4I system, and introduces their features and applications, and examines the challenges associated with each. Recognition these models and architectures is the way for proper planning to select an optimal and efficient model for assessing the threat of different targets in multi-sensor integrated networks in C4I systems.