An Intelligent System For High Resolution Radar Systems

Cognitive radio is a recent, novel approach that integrates machine perception software into wireless systems. The term cognitive radio was first used by Joe Mitola. The concept and the term cognitive radio quickly caught the attention and interest of many in the communications field. Cognitive radios are capable of making decisions and selecting or modifying the operating parameters of a radio. Given these capabilities, it is feasible to build a cognitive radar system as introduced by Simon Haykin in 2006. Cognitive radar, as described by Haykin, is an intelligent system that must be aware of its environment, uses prior knowledge, and builds on learning through interaction of the radar with the environment. The main objective of this Dissertation is to develop an intelligent system for adaptive high-resolution radar with cognitive capabilities that has the potential for providing intelligent decisions making process to determine the optimal mode of operation the radar should operate in a given environment. An intelligent system model with a cognitive engine is developed to create a radar with cognitive capabilities, thereby allowing the radar to have awareness of its environment and to adapt its operating characteristics, take action, and learn from experience gained. A cognitive engine determines the optimal system parameters for performing autonomous tasks using the information collected from the participant engines. The functionalities of the engine are identified and presented. The design and analysis of its performance is discussed and a specific application of airborne surveillance on a dessert environment, based on the proposed cognitive engine in intelligent radar system, is demonstrated