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Author: Jonathan J. Preussner Publisher: ISBN: Category : Automatic tracking Languages : en Pages :
Book Description
ABSTRACT: Human classification is a valuable tactical tool for military and security applications. Multiple target tracking is inherent to target classification in the radar system. A target tracker is designed in Matlab. It uses a simplified Kalman filter to predict range and velocities for multiple targets. Multiple target tracking allows several targets to be tracked and classified simultaneously. The thesis research addresses the design and implementation of human classifiers. The classification algorithms all use Spectrogram data to classify targets. The Fourier transform method classifies human targets by the periodic motions of human gait. Emphasis will be placed on optimizing the algorithm for implementation in a digital signal processor. Detemining targets' angles of incidence is also discussed. Additional improvements in the application of this classifier are made to reduce the required computational and storage resources. A template matching algorithm is also researched. The template matching method uses previously recorded sets of data to classify targets. This algorithm will be designed for near-real time classification of human and non-human targets. All classification methods require multiple-target tracking to generate Spectrograms for classification.
Author: Jonathan J. Preussner Publisher: ISBN: Category : Automatic tracking Languages : en Pages :
Book Description
ABSTRACT: Human classification is a valuable tactical tool for military and security applications. Multiple target tracking is inherent to target classification in the radar system. A target tracker is designed in Matlab. It uses a simplified Kalman filter to predict range and velocities for multiple targets. Multiple target tracking allows several targets to be tracked and classified simultaneously. The thesis research addresses the design and implementation of human classifiers. The classification algorithms all use Spectrogram data to classify targets. The Fourier transform method classifies human targets by the periodic motions of human gait. Emphasis will be placed on optimizing the algorithm for implementation in a digital signal processor. Detemining targets' angles of incidence is also discussed. Additional improvements in the application of this classifier are made to reduce the required computational and storage resources. A template matching algorithm is also researched. The template matching method uses previously recorded sets of data to classify targets. This algorithm will be designed for near-real time classification of human and non-human targets. All classification methods require multiple-target tracking to generate Spectrograms for classification.
Author: Rainer Stiefelhagen Publisher: Springer ISBN: 3540695680 Category : Computers Languages : en Pages : 370
Book Description
This book constitutes the thoroughly refereed post-proceedings of the First International CLEAR 2006 Evaluation Campaign and Workshop on Classification of Events, Activities and Relationships for evaluation of multimodal technologies for the perception of humans, their activities and interactions. The workshop was held in the UK in April 2006. The papers were carefully reviewed and selected for inclusion in the book.
Author: Avik Santra Publisher: Artech House ISBN: 1630817473 Category : Technology & Engineering Languages : en Pages : 358
Book Description
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.
Author: Mahendra Mallick Publisher: John Wiley & Sons ISBN: 1118450566 Category : Technology & Engineering Languages : en Pages : 569
Book Description
A unique guide to the state of the art of tracking, classification, and sensor management This book addresses the tremendous progress made over the last few decades in algorithm development and mathematical analysis for filtering, multi-target multi-sensor tracking, sensor management and control, and target classification. It provides for the first time an integrated treatment of these advanced topics, complete with careful mathematical formulation, clear description of the theory, and real-world applications. Written by experts in the field, Integrated Tracking, Classification, and Sensor Management provides readers with easy access to key Bayesian modeling and filtering methods, multi-target tracking approaches, target classification procedures, and large scale sensor management problem-solving techniques. Features include: An accessible coverage of random finite set based multi-target filtering algorithms such as the Probability Hypothesis Density filters and multi-Bernoulli filters with focus on problem solving A succinct overview of the track-oriented MHT that comprehensively collates all significant developments in filtering and tracking A state-of-the-art algorithm for hybrid Bayesian network (BN) inference that is efficient and scalable for complex classification models New structural results in stochastic sensor scheduling and algorithms for dynamic sensor scheduling and management Coverage of the posterior Cramer-Rao lower bound (PCRLB) for target tracking and sensor management Insight into cutting-edge military and civilian applications, including intelligence, surveillance, and reconnaissance (ISR) With its emphasis on the latest research results, Integrated Tracking, Classification, and Sensor Management is an invaluable guide for researchers and practitioners in statistical signal processing, radar systems, operations research, and control theory.
Author: Moeness Amin Publisher: CRC Press ISBN: 1498782000 Category : Technology & Engineering Languages : en Pages : 390
Book Description
This book aims to capture recent advances and breakthroughs in in-home radar monitoring of human motions and activities. It addresses three key attributes of radar for in-door human monitoring, namely: motion classification including fall, detection of vital signs, and categorization of human gait for risk assessment and progression of physical impairments and disabilities. It explores recent developments in radar technology for human monitoring inside homes and residences. The reader will learn enhanced detection and classification techniques of radar signals associated with human micro- and macro-motions. Furthermore, the book includes examples using real data collected from healthy individuals, patients, and retirement communities based on the subject Doppler and range information, and using different single and multi-antenna radar system configurations. Results are also presented using modeled data based on biomechanics and kinematics. Indoor monitoring is further demonstrated using alternative technologies of infrared sensors and RF signals of opportunities.
Author: Fulvio Gini Publisher: John Wiley & Sons ISBN: 0470283149 Category : Science Languages : en Pages : 287
Book Description
Discover the technology for the next generation of radar systems Here is the first book that brings together the key concepts essential for the application of Knowledge Based Systems (KBS) to radar detection, tracking, classification, and scheduling. The book highlights the latest advances in both KBS and radar signal and data processing, presenting a range of perspectives and innovative results that have set the stage for the next generation of adaptive radar systems. The book begins with a chapter introducing the concept of Knowledge Based (KB) radar. The remaining nine chapters focus on current developments and recent applications of KB concepts to specific radar functions. Among the key topics explored are: Fundamentals of relevant KB techniques KB solutions as they apply to the general radar problem KBS applications for the constant false-alarm rate processor KB control for space-time adaptive processing KB techniques applied to existing radar systems Integrated end-to-end radar signals Data processing with overarching KB control All chapters are self-contained, enabling readers to focus on those topics of greatest interest. Each one begins with introductory remarks, moves on to detailed discussions and analysis, and ends with a list of references. Throughout the presentation, the authors offer examples of how KBS works and how it can dramatically improve radar performance and capability. Moreover, the authors forecast the impact of KB technology on future systems, including important civilian, military, and homeland defense applications. With chapters contributed by leading international researchers and pioneers in the field, this text is recommended for both students and professionals in radar and sonar detection, tracking, and classification and radar resource management.
Author: Anthony K. Hyder Publisher: Springer Science & Business Media ISBN: 9401005567 Category : Computers Languages : en Pages : 929
Book Description
For some time, all branches of the military have used a wide range of sensors to provide data for many purposes, including surveillance, reconnoitring, target detection and battle damage assessment. Many nations have also attempted to utilise these sensors for civilian applications, such as crop monitoring, agricultural disease tracking, environmental diagnostics, cartography, ocean temperature profiling, urban planning, and the characterisation of the Ozone Hole above Antarctica. The recent convergence of several important technologies has made possible new, advanced, high performance, sensor based applications relying on the near-simultaneous fusion of data from an ensemble of different types of sensors. The book examines the underlying principles of sensor operation and data fusion, the techniques and technologies that enable the process, including the operation of 'fusion engines'. Fundamental theory and the enabling technologies of data fusion are presented in a systematic and accessible manner. Applications are discussed in the areas of medicine, meteorology, BDA and targeting, transportation, cartography, the environment, agriculture, and manufacturing and process control.
Author: Wolfgang Koch Publisher: Springer Science & Business Media ISBN: 3642392717 Category : Technology & Engineering Languages : en Pages : 261
Book Description
Sensor Data Fusion is the process of combining incomplete and imperfect pieces of mutually complementary sensor information in such a way that a better understanding of an underlying real-world phenomenon is achieved. Typically, this insight is either unobtainable otherwise or a fusion result exceeds what can be produced from a single sensor output in accuracy, reliability, or cost. This book provides an introduction Sensor Data Fusion, as an information technology as well as a branch of engineering science and informatics. Part I presents a coherent methodological framework, thus providing the prerequisites for discussing selected applications in Part II of the book. The presentation mirrors the author's views on the subject and emphasizes his own contributions to the development of particular aspects. With some delay, Sensor Data Fusion is likely to develop along lines similar to the evolution of another modern key technology whose origin is in the military domain, the Internet. It is the author's firm conviction that until now, scientists and engineers have only scratched the surface of the vast range of opportunities for research, engineering, and product development that still waits to be explored: the Internet of the Sensors.
Author: Jonathan J. Preussner
Author: Jonathan J. Preussner
Author: Stephen L. Johnston
Author: Rainer Stiefelhagen
Author: Avik Santra
Author: Mahendra Mallick
Author: Moeness Amin
Author: Fulvio Gini
Author: 
Author: Anthony K. Hyder
Author: Wolfgang Koch