Smart Sensing and Communications for UAVs/Drones

Abstract

Reliable sensing and energy-efficient communication are an integral part of unmanned aerial vehicle (UAV)-based applications. However, it is challenging to ensure reliable sensing under all weather conditions. Furthermore, enabling robust and energy-efficient communication of this sensed data for seamless autonomous operations is equally demanding. Low-complexity and lightweight algorithms play a vital role in this regard. As a result, the goal of this Ph.D. research project is to design, develop, and implement reliable sensing and energy-efficient communication techniques to provide seamless autonomous operations for UAVs and ground control stations. To achieve the intended goal, one of the objectives is directed toward developing novel lightweight low-complexity smart sensing algorithms that attain improved detection performance in adverse weather and lighting conditions too. In this regard, this research focuses on utilizing thermal, acoustic, and mmWave frequency-modulated continuous wave (FMCW) radar sensors with lightweight machine learning algorithms to obtain improved detection and localization performance. The sensed information along with telemetry data is required to be transmitted to other UAVs or ground control stations to facilitate efficient and secure coordination of autonomous UAVs. Hence, the secondary objective of this research addresses the challenge of achieving energy-efficient data transmission for a UAV-assisted wireless network. The research for attaining energy-efficient data transmission focuses on the design of a dynamic and adaptively optimized switching algorithm that leverages the distinct features of the various onboard communication modules. This thesis is a compendium of seven publications that are organized into five chapters. Overall the primary objective is to develop reliable smart sensing algorithms along with energy-efficient communication schemes to enable seamless autonomous UAV operations. The first chapter briefly introduces the various challenges dealt in the thesis and provides an overview of the thesis structure. Chapter 2 provides the necessary literary material to navigate the subsequent chapters. Chapter 3 discusses three sensing approaches using thermal, acoustic, and mmWave FMCW radar sensors to achieve improved detection and localization performance. In chapter 4, the notion of an adaptively optimized switching algorithm for energyefficient communication is conceived. Two approaches to form the hybrid communication switching network are discussed. Finally, chapter 5 concludes the Ph.D. dissertation by summarizing the proposed approaches and providing avenues for future research.