This unique resource presents the principles of meter wave ground imaging radar focusing on foliage penetration. Scattering of VHF/UHF radar signals are presented including the basic laws of electromagnetism, homogeneous media, media discontinuities/non-flat media discontinuities, and ground reflectivity. The book introduces meter wavelength synthetic aperture radar, bandwidth, and SAR imaging principles, including moving objects and also compares collected SAR data. Meter wavelength SAR system design and processing is explored, highlighting low frequency SAR design aspects, characterization of additive noise, antenna system basics, waveforms and emission adaptation which is critical material to the advancement in sensors and signal processing for below ground imaging by the energy industry and governments worldwide. The FFBP method of processing, explicit treatment of base 2 FFBP is explained along with motion errors sensitivity and motion estimation methods. The book also explains the Bayesian change detection, covariance moving target extraction and polarimetric subsurface imaging.

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 is the first book to bring together the increasingly complex radar automotive technologies and tools being explored and utilized in the development of fully autonomous vehicles – technologies and tools now understood to be an essential need for the field to fully mature. The book presents state-of-the-art knowledge as shared by the best and brightest experts working in the automotive radar industry today -- leaders who have “been there and done that.” Each chapter is written as a standalone "master class" with the authors, seeing the topic through their eyes and experiences. Where beneficial, the chapters reference one another but can otherwise be read in any order desired, making the book an excellent go-to reference for a particular topic or review you need to understand. You’ll get a big-picture tour of the key radar needs for fully autonomous vehicles, and how achieving these needs is complicated by the automotive environment’s dense scenes, number of possible targets of interest, and mix of very large and very small returns. You’ll then be shown the challenges from – and mitigations to – radio frequency interference (RFI), an ever-increasing challenge as the number of vehicles with radars – and radars per vehicle grow. The book also dives into the impacts of weather on radar performance, providing you with insights gained from extensive real-world testing. You are then taken through the integration and systems considerations, especially regarding safety, computing needs, and testing. Each of these areas is influenced heavily by the needs of fully autonomous vehicles and are open areas of research and development. With this authoritative volume you will understand: * How to engage with radar designers (from a system integrator / OEM standpoint); * How to structure and set requirements for automotive radars; * How to address system safety needs for radars in fully autonomous vehicles; * How to assess weather impact on the radar and its ability to support autonomy; * How to include weather effects into specifications for radars. This is an essential reference for engineers currently in the autonomous vehicle arena and/or working in automotive radar development, as well as engineers and leaders in adjacent radar fields needing to stay abreast of the rapid developments in this exciting and dynamic field of research and development.

This cutting-edge resource introduces the basic concepts of passive bistatic radar, such as bistatic geometry, bistatic radar equation and analysis of different illuminating signals. These techniques, although known for almost a century, have not been developed intensively for decades, mainly due to technical limitations, but today, the passive radar concept can be realized in practice, and is of great interest for military and civilian users. This book provides insight into understanding the potential and limitations of passive radar systems, as well as the differences between signal processing in active and passive radar. Each of the signal processing stages typically applied in passive radar is described, including digital beamforming, clutter removal, target detection, localization and tracking. These concepts are illustrated with both simulated and measured data along with examples of passive radar systems. Correlation processing, which is crucial for passive radar operation, is presented, as well as practical approaches for calculating the cross-ambiguity function. The problems of range and velocity-cell migration are also introduced. The book analyzes and compares different antenna array geometries to show readers the appropriate solution for a particular scenario of passive radar. Cartesian tracking is also presented, based on the extended Kalman filter. Parallel and sequential updating approaches are introduced and compared. These concepts are illustrated with both simulated and measured data along with examples of passive radar systems, making this book useful for both novice and advanced practitioners.

Non-Line-of-Sight Radar is the first book on the new and exciting area of detecting and tracking targets via radar multipath without direct-line-of-sight (DLOS). This revolutionary capability is finding new applications in the tracking of objects in non-line-of-sight (NLOS) urban environments including detection and tracking of UAVs. This book brings together for the first time all the essential underpinnings and techniques required to develop and field a viable NLOS radar. It presents many examples, including electromagnetic radiation propagation in urban NLOS environments, extracting building location and morphology from readily available terrain databases, predictive ray-tracing techniques, and multi-target NLOS tracking. Readers will learn how to apply radar to urban tracking that was previously deemed impossible. The book shows how real-time physics calculations can be incorporated into the radar processor, and how existing radar hardware can be adopted for non-line-of-sight radar use without major upgrades. Including results from both high-fidelity, physics-based simulations and actual flight test data, this book establishes the efficacy of NLOS radar in practical applications.

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.

Written by a prominent expert in the field, this updated and expanded second edition of an Artech House classic includes the most recent breakthroughs in vital sign and gender recognition via micro-radar, as well as covering basic principles of Doppler effect and micro-Doppler effect and describing basic applications of micro-Doppler signatures in radar. The book presents detailed procedures about how to generate and analyze micro-Doppler signatures from radar signals. Readers will learn how to model and animate an object (such as human, spinning top, rotating rotor blades) with movement, simulation of radar returns from the object, and generating micro-Doppler signature. The book includes coverage of the Google project “Soli”, which demonstrated the use of radar micro-Doppler effect to sense and recognize micro motions of human hand gesture for controlling devices. It also discusses noncontact detection of human vital sign (micro motions of breathing and heart beating) using radar, another important application of radar micro-Doppler sensors. Detailed MATLAB source codes for simulation of radar backscattering from targets with various motions are provided, along with source codes for generating micro-Doppler signatures and analyzing characteristics of targets.

This highly-anticipated second edition of an Artech House classic covers several key radar analysis areas: the radar range equation, detection theory, ambiguity functions, waveforms, antennas, active arrays, receivers and signal processors, CFAR and chaff analysis. Readers will be able to predict the detection performance of a radar system using the radar range equation, its various parameters, matched filter theory, and Swerling target models. The performance of various signal processors, single pulse, pulsed Doppler, LFM, NLFM, and BPSK, are discussed, taking into account factors including MTI processing, integration gain, weighting loss and straddling loss. The details of radar analysis are covered from a mathematical perspective, with in-depth breakdowns of radar performance in the presence of clutter. Readers will be able to determine the nose temperature of a multi-channel receiver as it is used in active arrays. With the addition of three new chapters on moving target detectors, inverse synthetic aperture radar (ISAR) and constant false alarm rate (CFAR) and new MATLAB codes, this expanded second edition will appeal to the novice as well as the experienced practitioner.

Unmanned aerial systems (UAS) have evolved rapidly in recent years thanks to advances in microelectromechanical components, navigation, perception, and artificial intelligence, allowing for a fast development of autonomy. This book presents general approaches to develop, test, and evaluate critical functions such as navigation, obstacle avoidance and perception, and the capacity to improve performance in real and simulated scenarios. It provides the practical knowledge to install, analyze and evaluate UAS solutions working in real systems; illustrates how to use and configure complete platforms and software tools; and reviews the main enabling technologies applied to develop UAS, possibilities and evaluation methodology. You will get the tools you need to evaluate navigation and obstacle avoidance functions, object detection, and planning and landing alternatives in simulated conditions. The book also provides helpful guidance on the integration of additional sensors (video, weather, meteorological) and communication networks to build IoT solutions. This is an important book for practitioners and researchers interested in integrating advanced techniques in the fields of AI, sensor fusion and mission management, and anyone interest in applying and testing advanced algorithms in UAS platforms.

This new resource covers a wide range of content by focusing on theorems and examples to explain key concepts of signals and linear systems theory in fewer than 300 pages. Readers will learn how to compute the impulse response of an electronic circuit, design a filter in the presence of colored noise, and use the Z transform to design a digital filter. The book covers transform theory and statespace analysis and design. Stochastic systems and signals, a topic that has become important recently with the advent of renewable energy, is also presented. The Ergodic theorem is discussed in detail, with specific, real world examples of its application to renewable power and energy systems as well as signal processing systems. The book also provides a self-contained introduction to the theory of probability. Written for the practicing engineer and the student new to the subject, this comprehensive guide includes links to literature and online resources for the reader who wants additional information. In addition to numerous worked examples, this primer includes MATLAB® source code to assist readers with their projects in the field.