Deep Learning Applications Of Short Range Radars
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Deep Learning Applications Of Short Range Radars
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Author : Avik Santra
language : en
Publisher: Artech House
Release Date : 2020-09-30
Deep Learning Applications Of Short Range Radars written by Avik Santra and has been published by Artech House this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-30 with Technology & Engineering categories.
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.
Deep Learning For Radar And Communications Automatic Target Recognition
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Author : Uttam K. Majumder
language : en
Publisher: Artech House
Release Date : 2020-07-31
Deep Learning For Radar And Communications Automatic Target Recognition written by Uttam K. Majumder and has been published by Artech House this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-31 with Technology & Engineering categories.
This authoritative resource presents a comprehensive illustration of modern Artificial Intelligence / Machine Learning (AI/ML) technology for radio frequency (RF) data exploitation. It identifies technical challenges, benefits, and directions of deep learning (DL) based object classification using radar data, including synthetic aperture radar (SAR) and high range resolution (HRR) radar. The performance of AI/ML algorithms is provided from an overview of machine learning (ML) theory that includes history, background primer, and examples. Radar data issues of collection, application, and examples for SAR/HRR data and communication signals analysis are discussed. In addition, this book presents practical considerations of deploying such techniques, including performance evaluation, energy-efficient computing, and the future unresolved issues.
Contributions To Machine Learning In Automotive Camera And Radar Perception Systems
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Author : Weimeng Zhu
language : en
Publisher:
Release Date : 2023
Contributions To Machine Learning In Automotive Camera And Radar Perception Systems written by Weimeng Zhu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.
Deep Learning For Radar Signal Processing
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Author : Michael K. Wharton
language : en
Publisher:
Release Date : 2021
Deep Learning For Radar Signal Processing written by Michael K. Wharton and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Deep learning (Machine learning) categories.
We address the current approaches to radar signal processing, which model radar signals with several assumptions (e.g., sparse or synchronized signals) that limit their performance and use in practical applications. We propose deep learning approaches to radar signal processing which do not make such assumptions. We present well-designed deep networks, detailed training procedures, and numerical results which show our deep networks outperform current approaches. In the first part of this thesis, we consider synthetic aperture radar (SAR) image recovery and classification from sub-Nyquist samples, i.e., compressive SAR. Our approach is to first apply back-projection and then use a deep convolutional neural network (CNN) to de-alias the result. Importantly, our CNN is trained to be agnostic to the subsampling pattern. Relative to the basis pursuit (i.e., sparsity-based) approach to compressive SAR recovery, our CNN-based approach is faster and more accurate, in terms of both image recovery MSE and downstream classification accuracy, on the MSTAR dataset. In the second part of this thesis, we consider the problem of classifying multiple overlapping phase-modulated radar waveforms given raw signal data. To do this, we design a complex-valued residual deep neural network and apply data augmentations during training to make our network robust to time synchronization, pulse width, and SNR. We demonstrate that our optimized network significantly outperforms the current state-of-the-art in terms of classification accuracy, especially in the asynchronous setting.
Radar Data Processing With Applications
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Author : He You
language : en
Publisher: John Wiley & Sons
Release Date : 2016-08-01
Radar Data Processing With Applications written by He You and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-01 with Technology & Engineering categories.
Radar Data Processing with Applications Radar Data Processing with Applications He You, Xiu Jianjuan, Guan Xin, Naval Aeronautical and Astronautical University, China A summary of thirty years’ worth of research, this book is a systematic introduction to the theory, development, and latest research results of radar data processing technology. Highlights of the book include sections on data pre-processing technology, track initiation, and data association. Readers are also introduced to maneuvering target tracking, multiple target tracking termination, and track management theory. In order to improve data analysis, the authors have also included group tracking registration algorithms and a performance evaluation of radar data processing. Presents both classical theory and development methods of radar data processing Provides state-of-the-art research results, including data processing for modern radars and tracking performance evaluation theory Includes coverage of performance evaluation, registration algorithm for radar networks, data processing of passive radar, pulse Doppler radar, and phased array radar Features applications for those engaged in information engineering, radar engineering, electronic countermeasures, infrared techniques, sonar techniques, and military command Radar Data Processing with Applications is a handy guide for engineers and industry professionals specializing in the development of radar equipment and data processing. It is also intended as a reference text for electrical engineering graduate students and researchers specializing in signal processing and radars.
Methods And Techniques In Deep Learning
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Author : Avik Santra
language : en
Publisher: John Wiley & Sons
Release Date : 2022-11-21
Methods And Techniques In Deep Learning written by Avik Santra and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-21 with Technology & Engineering categories.
Methods and Techniques in Deep Learning Introduces multiple state-of-the-art deep learning architectures for mmWave radar in a variety of advanced applications Methods and Techniques in Deep Learning: Advancements in mmWave Radar Solutions provides a timely and authoritative overview of the use of artificial intelligence (AI)-based processing for various mmWave radar applications. Focusing on practical deep learning techniques, this comprehensive volume explains the fundamentals of deep learning, reviews cutting-edge deep metric learning techniques, describes different typologies of reinforcement learning (RL) algorithms, highlights how domain adaptation (DA) can be used for improving the performance of machine learning (ML) algorithms, and more. Throughout the book, readers are exposed to product-ready deep learning solutions while learning skills that are relevant for building any industrial-grade, sensor-based deep learning solution. A team of authors with more than 70 filed patents and 100 published papers on AI and sensor processing illustrates how deep learning is enabling a range of advanced industrial, consumer, and automotive applications of mmWave radars. In-depth chapters cover topics including multi-modal deep learning approaches, the elemental blocks required to formulate Bayesian deep learning, how domain adaptation (DA) can be used for improving the performance of machine learning algorithms, and geometric deep learning are used for processing point clouds. In addition, the book: Discusses various advanced applications and how their respective challenges have been addressed using different deep learning architectures and algorithms Describes deep learning in the context of computer vision, natural language processing, sensor processing, and mmWave radar sensors Demonstrates how deep parametric learning reduces the number of trainable parameters and improves the data flow Presents several human-machine interface (HMI) applications such as gesture recognition, human activity classification, human localization and tracking, in-cabin automotive occupancy sensing Methods and Techniques in Deep Learning: Advancements in mmWave Radar Solutions is an invaluable resource for industry professionals, researchers, and graduate students working in systems engineering, signal processing, sensors, data science, and AI.
Deep Learning For Weak Target Detection In Range Doppler Data
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Author : Bibi M. Dang
language : en
Publisher:
Release Date : 2022
Deep Learning For Weak Target Detection In Range Doppler Data written by Bibi M. Dang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Doppler radar categories.
Micro Doppler Radar And Its Applications
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Author : Francesco Fioranelli
language : en
Publisher: SciTech Publishing
Release Date : 2020-09-14
Micro Doppler Radar And Its Applications written by Francesco Fioranelli and has been published by SciTech Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-14 with Technology & Engineering categories.
This book covers the latest developments in radar micro-Doppler signatures and non-cooperative recognition of moving targets, for researchers and advanced students of radar systems. Micro-Doppler signatures is a very broad topic with applications in healthcare, security and surveillance. Edited by leading researchers in the field, the book consists of a series of chapters with contributions from different groups of authors who are international experts on their topics. The following topics are covered: multistatic radar micro-Doppler; passive radar approaches for healthcare; sparsity-driven methods for micro-Doppler detection and classification; deep neural networks for radar micro-Doppler signature classification; classification of personnel for ground-based surveillance; multimodal sensing for assisted living using radar; micro-Doppler analysis of ballistic targets; small drones and bird signatures as emerging targets; hardware development and applications of portable FMCW radars; digital-IF CW Doppler radar and its contactless healthcare sensing; L1-norm principal component and discriminant analyses of micro-Doppler signatures for indoor human activity recognition; and micro-Doppler signature extraction and analysis for automotive application. Finally, the editors have written a concluding short chapter that brings together an overview of the field and discusses likely future trends.
Engineering Uas Applications Sensor Fusion Machine Vision And Mission Management
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Author : Jesús Garcia
language : en
Publisher: Artech House
Release Date : 2023-07-31
Engineering Uas Applications Sensor Fusion Machine Vision And Mission Management written by Jesús Garcia and has been published by Artech House this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-31 with Technology & Engineering categories.
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.
Adaptive Radar Detection Model Based Data Driven And Hybrid Approaches
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Author : Angelo Coluccia
language : en
Publisher: Artech House
Release Date : 2022-11-30
Adaptive Radar Detection Model Based Data Driven And Hybrid Approaches written by Angelo Coluccia and has been published by Artech House this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-30 with Technology & Engineering categories.
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.