(a)Statement of Problem. EW has grown to become an important component of military operations. It includes three major subdivisions: electronic support(ES), electronic attack (EA) and electronic protection(EP) for either offensive or defensive operations thus to prevent hostile use, retain friendly use of the EMS. An EW system consists of antenna(s), receiver(s), processing unit(s), and database to provide the means to intercept, identify, analyze and locate radiated electromagnetic energy, and then deploy countermeasures. Historically, EW systems were developed based on knowledge of specific, previously learned threats. The received RF signals are processed, analyzed, and categorized as either threatening or non-threatening associated with actions to be taken. The database contains two tables, one stores previous known threats that the system had been thoroughly tested against, while the other contains the corresponding pre-programmed countermeasure techniques. Thus, there exists a close cooperation between ES and EA divisions. Figure below shows a block diagram of conventional EW system. (b) A hypothesis is that this challenge can be effectively addressed with cognitive technology by sensing, adapting and learning environment changes and possible interference, and embodying a feedback-based decision-making mechanism to intelligently deploy optimal countermeasures. Figure below shows a block diagram of generic Cognitive Electronic Warfare (CEW) system. In the system, Environmental Perception focuses on sensing of the operational environment and observing the changes to optimize further processing procedures. Intelligent Signal Characterization uses machine learning algorithms to assess and characterize EMS signals and classifies them as either known or unknown threats. The objective of the Cognitive Electronic Attack (CEA) module is to synthesize close-to-optimal countermeasures subject to transceiver limitations, user-input restrictions and performance goals. Dynamic Knowledge Base contains not only a priori information of environmental and target aspects, but also information on recently learned threats. The feedback loop plays a key role in monitoring and evaluating the jamming performance, and adjusting the transmission parameters to achieve optimal effectiveness. The ES and EA modules need to be enhanced with cognitive algorithms and act together synchronously and co-ordinately. This collaboration ensures the system could identify source and intent of signals in a highly dense RF environment, and decide where and how to apply countermeasures to achieve optimum effects. In other words, the said capability boils down to intelligent threat identification, target acquisition with location fixing, orientation of ECM/Jammer resources and autonomous coordinated soft kill option to neutralise the threat