DEVELOPMENT OF EM BASED TECHNIQUES WITH MACHINE LEARNING FOR DESIGNING THE MICROWAVE STRUCTURES

Abstract

Microwaves due to their frequency range and EM properties find their application in various civil, industrial, and military fields. One of the first major advancements in microwave technology was the creation of RADAR, which opened the door for its widespread applications. Since then, numerous microwave structures have been created to suit a variety of applications. To accomplish the objective of focusing or directing the energy in a particular direction or decreasing reflection or interference, microwave structures (MS) are made to control the transmission and absorption of microwaves. As the use of microwaves continues to expand, the need for more advanced and sophisticated structures has also increased. Hence, there is a dire need to develop and evolve the techniques to keep up with the demands of ever-widening application specific MS. There are several techniques used for the development of microwave absorbing structures (MASs), such as impedance matching, camouflaging, multilayering, frequency selective surfaces (FSS) etc. Similarly, transmissive structures use single layer, multilayer, and FSS type structures. These methods can be combined to create microwave absorptive/ transmissive structures that have a high absorption rate and a wide bandwidth for absorption/ transmission. The microwave structures can be used for a variety of purposes, including camouflaging, EMI shielding, designing anechoic chambers, radomes, and many other applications. The primary focus of this thesis is to design microwave absorptive/ transmissive structures and camouflage nets. For this purpose, we have explored the use of methodologies like dielectric mixing model and resin film infusion (RFI), and advanced electromagnetic (EM) techniques like multilayering and FSS. The thesis focuses on the development of multilayered MAS that can be used to design the strategic parts of military equipment and simulation analysis to design a camouflage net in the microwave region by using microwave absorbing material (MAM) impregnated cloth fabric. Two microwave transmissive structures are also developed for a wideband microwave transmission followed by using the machine learning (ML) tool to determine the FSS parameters for the user specific applications. Chapter 1 introduces the topic and gives a technical insight of microwave and its applications. It presents various microwave absorption mechanisms and advanced EM techniques that are used to enhance the performance of MS. It presents relevant theoretical background for the considered objectives which includes the principle of wave absorption in terms of impedance matching, wave dissipation, and other types of microwaves absorbing techniques. The chapter also emphasizes various motivating topics and related problem statements for conducting the present study. It entails the framework of the research that has been followed to achieve the objective.