Fully-Adaptive Radar Modeling and Simulation Development

The goal of this project is to develop a modeling and simulation (M&S) capability for distributed, fully adaptive radar (FAR) that will enable algorithm development and testing on simulated, previously collected, and real-time experimental data.In Phase I, we developed a FAR M&S software architecture that models the key system components of the perception-action (PA) cycle of cognition.The FAR M&S architecture is coded in MATLAB using an object oriented programming approach.It includes a FAR engine to control the operation of the PA cycle and software objects that model system components.A separate module implements the objects to perform processing of simulated and real-time data from the Cognitive Radar Engineering Workspace (CREW) at Ohio State University.The FAR M&S architecture allows for transparent switching between the simulated and experimental CREW data sources, as well as between FAR algorithms that drive the sensing.In Phase II, the CREW module will be further developed to run multi-target, multi-sensor, multi-parameter FAR algorithms on both simulated and experimental data. A new module will be developed for a dynamic, distributed airborne multiple input multiple output (MIMO) radar FAR system, and techniques to improve the computational efficiency and user-friendliness of the code will be incorporated.