In recent years, advances in radio detection and ranging technology, sustained by new achievements in the fields of signal processing and electronic components, have permitted the adoption of radars in many civil and defense applications. This resource discusses how highly integrated radar has been adopted by several new markets such as contactless vital sign monitoring (heart rate, breath rate) or harbour traffic control, as well as several applications for vehicle driver assistance. You are provided with scenarios, applications, and requirements, while focusing on the trade-offs between flexibility, programmability, power consumption, size and weight, and complexity.
This book provides a thorough overview of cutting-edge research on electronics applications relevant to industry, the environment, and society at large. A wide spectrum of application domains are covered, from automotive to space and from health to security and special attention is devoted to the use of embedded devices and sensors for imaging, communication and control. The book is based on the 2014 APPLEPIES Conference, held in Rome, which brought together researchers and stakeholders to consider the most significant current trends in the field of applied electronics and to debate visions for the future. Areas covered by the conference included information communication technology; biotechnology and biomedical imaging; space; secure, clean and efficient energy; the environment; and smart, green and integrated transport. As electronics technology continues to develop apace, constantly meeting previously unthinkable targets, further attention needs to be directed toward the electronics applications and the development of systems that facilitate human activities. This book, written by industrial and academic professionals, will hopefully contribute in this endeavor.
Enabling Technologies for the Internet of Things: Wireless Circuits, Systems and Networks collects slides and notes from the lectures given in the 2017 Seasonal School Enabling Technologies for the Internet-of-Things, supported by IEEE CAS Society and by INTEL funding, and organized by Prof. Sergio Saponara, and Prof. Giuliano Manara. The book discusses new trends in Internet-of-Things (IoT) technologies, considering technological and training aspects, with special focus on electronic and electromagnetic circuits and systems. IoT involves research and design activities both in analog and in digital circuit/signal domains, including focus on sensors interfacing and conditioning, energy harvesting, low-power signal processing, wireless connectivity and networking, functional safety (FuSa). FuSa is one of the emerging key issues in IoT applications in safety critical domain like industry 4.0, autonomous and connected vehicles and e-health. Our world is becoming more and more interconnected. Currently it is estimated that two hundred billion smart objects will be part of the IoT by 2020. This new scenario will pave the way to innovative business models and will bring new experiences in everyday life. The challenge is offering products, services and comprehensive solutions for the IoT, from technology to intelligent and connected objects and devices to connectivity and data centers, enhancing smart home, smart factory, autonomous driving cars and much more, while at the same time ensuring the highest safety standards. In safety-critical contexts, where a fault could jeopardize the human life, safety becomes a key aspect.
This book highlights the application of active array antennas in high-resolution microwave imaging radar systems. It introduces the basic principles, analytical methods, and performance parameters of active array antennas to achieve low profile, high efficiency, and lightweight. The book systematically elaborates the architecture, analysis, and engineering practice to achieve wideband, multi-band, multi-polarization, and common aperture in active array antennas. It explores hotspot technologies of digital array antennas, microwave photonic array antennas, and active packaging antennas. By presenting over 300 illustrations and diagrams, including schematic diagrams, block diagrams, relation diagrams, and breakdown drawings, the book enables a thorough understanding of the antenna array microsystem as the advanced phase of active array antennas and the direction of future R&D. The book is a good reference source for researchers and engineers interested in the engineering and implementation of microwave imaging radar systems and antenna technology.
Academic Press Library in Signal Processing, Volume 7: Array, Radar and Communications Engineering is aimed at university researchers, post graduate students and R&D engineers in the industry, providing a tutorial-based, comprehensive review of key topics and technologies of research in Array and Radar Processing, Communications Engineering and Machine Learning. Users will find the book to be an invaluable starting point to their research and initiatives. With this reference, readers will quickly grasp an unfamiliar area of research, understand the underlying principles of a topic, learn how a topic relates to other areas, and learn of research issues yet to be resolved. - Presents a quick tutorial of reviews of important and emerging topics of research - Explores core principles, technologies, algorithms and applications - Edited and contributed by international leading figures in the field - Includes comprehensive references to journal articles and other literature upon which to build further, more detailed knowledge
This book shows you how to adopt data-driven techniques for the problem of radar detection, both per se and in combination with model-based approaches. In particular, the focus is on space-time adaptive target detection against a background of interference consisting of clutter, possible jammers, and noise. It is a handy, concise reference for many classic (model-based) adaptive radar detection schemes as well as the most popular machine learning techniques (including deep neural networks) and helps you identify suitable data-driven approaches for radar detection and the main related issues. You’ll learn how data-driven tools relate to, and can be coupled or hybridized with, traditional adaptive detection statistics; understand fundamental concepts, schemes, and algorithms from statistical learning, classification, and neural networks domains. The book also walks you through how these concepts and schemes have been adapted for the problem of radar detection in the literature and provides you with a methodological guide for the design, illustrating different possible strategies. You’ll be equipped to develop a unified view, under which you can exploit the new possibilities of the data-driven approach even using simulated data. This book is an excellent resource for Radar professionals and industrial researchers, postgraduate students in electrical engineering and the academic community.
This exciting new resource covers various emerging applications of short range radars, including people counting and tracking, gesture sensing, human activity recognition, air-drawing, material classification, object classification, vital sensing by extracting features such as range-Doppler Images (RDI), range-cross range images, Doppler Spectrogram or directly feeding raw ADC data to the classifiers. The book also presents how deep learning architectures are replacing conventional radar signal processing pipelines enabling new applications and results. It describes how deep convolutional neural networks (DCNN), long-short term memory (LSTM), feedforward networks, regularization, optimization algorithms, connectionist This exciting new resource presents emerging applications of artificial intelligence and deep learning in short-range radar. The book covers applications ranging from industrial, consumer space to emerging automotive applications. The book presents several human-machine interface (HMI) applications, such as gesture recognition and sensing, human activity classification, air-writing, material classification, vital sensing, people sensing, people counting, people localization and in-cabin automotive occupancy and smart trunk opening. The underpinnings of deep learning are explored, outlining the history of neural networks and the optimization algorithms to train them. Modern deep convolutional neural network (DCNN), popular DCNN architectures for computer vision and their features are also introduced. The book presents other deep learning architectures, such as long-short term memory (LSTM), auto-encoders, variational auto-encoders (VAE), and generative adversarial networks (GAN). The application of human activity recognition as well as the application of air-writing using a network of short-range radars are outlined. This book demonstrates and highlights how deep learning is enabling several advanced industrial, consumer and in-cabin applications of short-range radars, which weren't otherwise possible. It illustrates various advanced applications, their respective challenges, and how they are been addressed using different deep learning architectures and algorithms.
