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Book Kalman Filtering and Information Fusion

Download or read book Kalman Filtering and Information Fusion written by Hongbin Ma and published by Springer Nature. This book was released on 2019-11-27 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses a key technology for digital information processing: Kalman filtering, which is generally considered to be one of the greatest discoveries of the 20th century. It introduces readers to issues concerning various uncertainties in a single plant, and to corresponding solutions based on adaptive estimation. Further, it discusses in detail the issues that arise when Kalman filtering technology is applied in multi-sensor systems and/or multi-agent systems, especially when various sensors are used in systems like intelligent robots, autonomous cars, smart homes, smart buildings, etc., requiring multi-sensor information fusion techniques. Furthermore, when multiple agents (subsystems) interact with one another, it produces coupling uncertainties, a challenging issue that is addressed here with the aid of novel decentralized adaptive filtering techniques.Overall, the book’s goal is to provide readers with a comprehensive investigation into the challenging problem of making Kalman filtering work well in the presence of various uncertainties and/or for multiple sensors/components. State-of-art techniques are introduced, together with a wealth of novel findings. As such, it can be a good reference book for researchers whose work involves filtering and applications; yet it can also serve as a postgraduate textbook for students in mathematics, engineering, automation, and related fields.To read this book, only a basic grasp of linear algebra and probability theory is needed, though experience with least squares, navigation, robotics, etc. would definitely be a plus.

Book Kalman Filtering and Information Fusion

Download or read book Kalman Filtering and Information Fusion written by Hongbin Ma and published by Springer. This book was released on 2019-12-06 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses a key technology for digital information processing: Kalman filtering, which is generally considered to be one of the greatest discoveries of the 20th century. It introduces readers to issues concerning various uncertainties in a single plant, and to corresponding solutions based on adaptive estimation. Further, it discusses in detail the issues that arise when Kalman filtering technology is applied in multi-sensor systems and/or multi-agent systems, especially when various sensors are used in systems like intelligent robots, autonomous cars, smart homes, smart buildings, etc., requiring multi-sensor information fusion techniques. Furthermore, when multiple agents (subsystems) interact with one another, it produces coupling uncertainties, a challenging issue that is addressed here with the aid of novel decentralized adaptive filtering techniques.Overall, the book’s goal is to provide readers with a comprehensive investigation into the challenging problem of making Kalman filtering work well in the presence of various uncertainties and/or for multiple sensors/components. State-of-art techniques are introduced, together with a wealth of novel findings. As such, it can be a good reference book for researchers whose work involves filtering and applications; yet it can also serve as a postgraduate textbook for students in mathematics, engineering, automation, and related fields.To read this book, only a basic grasp of linear algebra and probability theory is needed, though experience with least squares, navigation, robotics, etc. would definitely be a plus.

Book Multi Sensor Information Fusion

Download or read book Multi Sensor Information Fusion written by Xue-Bo Jin and published by MDPI. This book was released on 2020-03-23 with total page 602 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes papers from the section “Multisensor Information Fusion”, from Sensors between 2018 to 2019. It focuses on the latest research results of current multi-sensor fusion technologies and represents the latest research trends, including traditional information fusion technologies, estimation and filtering, and the latest research, artificial intelligence involving deep learning.

Book Introduction and Implementations of the Kalman Filter

Download or read book Introduction and Implementations of the Kalman Filter written by Felix Govaers and published by BoD – Books on Demand. This book was released on 2019-05-22 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sensor data fusion is the process of combining error-prone, heterogeneous, incomplete, and ambiguous data to gather a higher level of situational awareness. In principle, all living creatures are fusing information from their complementary senses to coordinate their actions and to detect and localize danger. In sensor data fusion, this process is transferred to electronic systems, which rely on some "awareness" of what is happening in certain areas of interest. By means of probability theory and statistics, it is possible to model the relationship between the state space and the sensor data. The number of ingredients of the resulting Kalman filter is limited, but its applications are not.

Book Electric Vehicles and the Future of Energy Efficient Transportation

Download or read book Electric Vehicles and the Future of Energy Efficient Transportation written by Subramaniam, Umashankar and published by IGI Global. This book was released on 2021-04-16 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: The electric vehicle market has been gradually gaining prominence in the world due to the rise in pollution levels caused by traditional IC engine-based vehicles. The advantages of electric vehicles are multi-pronged in terms of cost, energy efficiency, and environmental impact. The running and maintenance cost are considerably less than traditional models. The harmful exhaust emissions are reduced, besides the greenhouse gas emissions, when the electric vehicle is supplied from a renewable energy source. However, apart from some Western nations, many developing and underdeveloped countries have yet to take up this initiative. This lack of enthusiasm has been primarily attributed to the capital investment required for charging infrastructure and the slow transition of energy generation from the fossil fuel to the renewable energy format. Currently, there are very few charging stations, and the construction of the same needs to be ramped up to supplement the growth of electric vehicles. Grid integration issues also crop up when the electric vehicle is used to either do supply addition to or draw power from the grid. These problems need to be fixed at all the levels to enhance the future of energy efficient transportation. Electric Vehicles and the Future of Energy Efficient Transportation explores the growth and adoption of electric vehicles for the purpose of sustainable transportation and presents a critical analysis in terms of the economics, technology, and environmental perspectives of electric vehicles. The chapters cover the benefits and limitations of electric vehicles, techno-economic feasibility of the technologies being developed, and the impact this has on society. Specific points of discussion include electric vehicle architecture, wireless power transfer, battery management, and renewable resources. This book is of interest for individuals in the automotive sector and allied industries, policymakers, practitioners, engineers, technicians, researchers, academicians, and students looking for updated information on the technology, economics, policy, and environmental aspects of electric vehicles.

Book Kalman Filtering

Download or read book Kalman Filtering written by Mohinder S. Grewal and published by John Wiley & Sons. This book was released on 2015-02-02 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt: The definitive textbook and professional reference on Kalman Filtering – fully updated, revised, and expanded This book contains the latest developments in the implementation and application of Kalman filtering. Authors Grewal and Andrews draw upon their decades of experience to offer an in-depth examination of the subtleties, common pitfalls, and limitations of estimation theory as it applies to real-world situations. They present many illustrative examples including adaptations for nonlinear filtering, global navigation satellite systems, the error modeling of gyros and accelerometers, inertial navigation systems, and freeway traffic control. Kalman Filtering: Theory and Practice Using MATLAB, Fourth Edition is an ideal textbook in advanced undergraduate and beginning graduate courses in stochastic processes and Kalman filtering. It is also appropriate for self-instruction or review by practicing engineers and scientists who want to learn more about this important topic.

Book Beyond the Kalman Filter  Particle Filters for Tracking Applications

Download or read book Beyond the Kalman Filter Particle Filters for Tracking Applications written by Branko Ristic and published by Artech House. This book was released on 2003-12-01 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: For most tracking applications the Kalman filter is reliable and efficient, but it is limited to a relatively restricted class of linear Gaussian problems. To solve problems beyond this restricted class, particle filters are proving to be dependable methods for stochastic dynamic estimation. Packed with 867 equations, this cutting-edge book introduces the latest advances in particle filter theory, discusses their relevance to defense surveillance systems, and examines defense-related applications of particle filters to nonlinear and non-Gaussian problems. With this hands-on guide, you can develop more accurate and reliable nonlinear filter designs and more precisely predict the performance of these designs. You can also apply particle filters to tracking a ballistic object, detection and tracking of stealthy targets, tracking through the blind Doppler zone, bi-static radar tracking, passive ranging (bearings-only tracking) of maneuvering targets, range-only tracking, terrain-aided tracking of ground vehicles, and group and extended object tracking.

Book Statistical Sensor Fusion

    Book Details:
  • Author : Christian Lundquist
  • Publisher :
  • Release : 2015-04-02
  • ISBN : 9789144100111
  • Pages : 280 pages

Download or read book Statistical Sensor Fusion written by Christian Lundquist and published by . This book was released on 2015-04-02 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Introduction and Implementations of the Kalman Filter

Download or read book Introduction and Implementations of the Kalman Filter written by Felix Govaers and published by . This book was released on 2019 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sensor data fusion is the process of combining error-prone, heterogeneous, incomplete, and ambiguous data to gather a higher level of situational awareness. In principle, all living creatures are fusing information from their complementary senses to coordinate their actions and to detect and localize danger. In sensor data fusion, this process is transferred to electronic systems, which rely on some ""awareness"" of what is happening in certain areas of interest. By means of probability theory and statistics, it is possible to model the relationship between the state space and the sensor data. The number of ingredients of the resulting Kalman filter is limited, but its applications are not.

Book Advances in Aerospace Guidance  Navigation and Control

Download or read book Advances in Aerospace Guidance Navigation and Control written by Bogusław Dołęga and published by Springer. This book was released on 2017-12-15 with total page 751 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first three CEAS (Counsil of European Aerospace Societies) Specialist Conferences on Guidance, Navigation and Control (CEAS EuroGNC) were held in Munich, Germany in 2011, in Delft, Netherlands in 2013 and in Toulouse, France in 2017. The Warsaw University of Technology (WUT) and the Rzeszow University of Technology (RzUT) accepted the challenge of jointly organizing the 4th edition. The conference aims to promote scientific and technical excellence in the fields of Guidance, Navigation and Control (GNC) in aerospace and other fields of technology. The Conference joins together the industry with the academia research. This book covers four main topics: Guidance and Control, Control Theory Application, Navigation, UAV Control and Dynamic. The papers included focus on the most advanced and actual topics in guidance, navigation and control research areas: · Control theory, analysis, and design · ; Novel navigation, estimation, and tracking methods · Aircraft, spacecraft, missile and UAV guidance, navigation, and control · Flight testing and experimental results · Intelligent control in aerospace applications · Aerospace robotics and unmanned/autonomous systems · Sensor systems for guidance, navigation and control · Guidance, navigation, and control concepts in air traffic control systems For the 4th CEAS Specialist Conference on Guidance, Navigation and Control the International Technical Committee established a formal review process. Each paper was reviewed in compliance with good journal practices by independent and anonymous reviewers. At the end of the review process papers were selected for publication in this book.

Book Networked Embedded Sensing and Control

Download or read book Networked Embedded Sensing and Control written by Panos J. Antsaklis and published by Lecture Notes in Control and Information Sciences. This book was released on 2006-04-21 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains the proceedings of the Workshop on Networked Embedded Sensing and Control. This workshop aims at bringing together researchers working on different aspects of networked embedded systems in order to exchange research experiences and to identify the main scientific challenges in this exciting new area.

Book Sensor and Data Fusion

Download or read book Sensor and Data Fusion written by Lawrence A. Klein and published by SPIE Press. This book was released on 2004 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book illustrates the benefits of sensor fusion by considering the characteristics of infrared, microwave, and millimeter-wave sensors, including the influence of the atmosphere on their performance. Applications that benefit from this technology include: vehicular traffic management, remote sensing, target classification and tracking- weather forecasting- military and homeland defense. Covering data fusion algorithms in detail, Klein includes a summary of the information required to implement each of the algorithms discussed, and outlines system application scenarios that may limit sensor size but that require high resolution data.

Book Intuitive Understanding of Kalman Filtering with MATLAB

Download or read book Intuitive Understanding of Kalman Filtering with MATLAB written by Armando Barreto and published by CRC Press. This book was released on 2020-09-06 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: The emergence of affordable micro sensors, such as MEMS Inertial Measurement Systems, are applied in embedded systems and Internet-of-Things devices. This has brought techniques such as Kalman Filtering, which are capable of combining information from multiple sensors or sources, to the interest of students and hobbyists. This book will explore the necessary background concepts, helping a much wider audience of readers develop an understanding and intuition that will enable them to follow the explanation for the Kalman Filtering algorithm. Key Features: Provides intuitive understanding of Kalman Filtering approach Succinct overview of concepts to enhance accessibility and appeal to a wide audience Interactive learning techniques with code examples Malek Adjouadi, PhD, is Ware Professor with the Department of Electrical and Computer Engineering at Florida International University, Miami. He received his PhD from the Electrical Engineering Department at the University of Florida, Gainesville. He is the Founding Director of the Center for Advanced Technology and Education funded by the National Science Foundation. His earlier work on computer vision to help persons with blindness led to his testimony to the U.S. Senate on the committee of Veterans Affairs on the subject of technology to help persons with disabilities. His research interests are in imaging, signal processing and machine learning, with applications in brain research and assistive technology. Armando Barreto, PhD, is Professor of the Electrical and Computer Engineering Department at Florida International University, Miami, as well as the Director of FIU’s Digital Signal Processing Laboratory, with more than 25 years of experience teaching DSP to undergraduate and graduate students. He earned his PhD in electrical engineering from the University of Florida, Gainesville. His work has focused on applying DSP techniques to the facilitation of human-computer interactions, particularly for the benefit of individuals with disabilities. He has developed human-computer interfaces based on the processing of signals and has developed a system that adds spatialized sounds to the icons in a computer interface to facilitate access by individuals with "low vision." With his research team, he has explored the use of Magnetic, Angular-Rate and Gravity (MARG) sensor modules and Inertial Measurement Units (IMUs) for human-computer interaction applications. He is a senior member of the Institute of Electrical and Electronics Engineers (IEEE) and the Association for Computing Machinery (ACM). Francisco R. Ortega, PhD, is an Assistant Professor at Colorado State University and Director of the Natural User Interaction Lab (NUILAB). Dr. Ortega earned his PhD in Computer Science (CS) in the field of Human-Computer Interaction (HCI) and 3D User Interfaces (3DUI) from Florida International University (FIU). He also held a position of Post-Doc and Visiting Assistant Professor at FIU. His main research area focuses on improving user interaction in 3DUI by (a) eliciting (hand and full-body) gesture and multimodal interactions, (b) developing techniques for multimodal interaction, and (c) developing interactive multimodal recognition systems. His secondary research aims to discover how to increase interest for CS in non-CS entry-level college students via virtual and augmented reality games. His research has resulted in multiple peer-reviewed publications in venues such as ACM ISS, ACM SUI, and IEEE 3DUI, among others. He is the first-author of the CRC Press book Interaction Design for 3D User Interfaces: The World of Modern Input Devices for Research, Applications and Game Development. Nonnarit O-larnnithipong, PhD, is an Instructor at Florida International University. Dr. O-larnnithipong earned his PhD in Electrical Engineering, majoring in Digital Signal Processing from Florida International University (FIU). He also held a position of Post-Doctoral Associate at FIU in 2019. His research has focused on (1) implementing the sensor fusion algorithm to improve orientation measurement using MEMS inertial and magnetic sensors and (2) developing a 3D hand motion tracking system using Inertial Measurement Units (IMUs) and infrared cameras. His research has resulted in multiple peer-reviewed publications in venues such as HCI-International and IEEE Sensors.

Book Multi Sensor Data Fusion

Download or read book Multi Sensor Data Fusion written by H.B. Mitchell and published by Springer Science & Business Media. This book was released on 2007-07-13 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a comprehensive introduction to the theories and techniques of multi-sensor data fusion. It is aimed at advanced undergraduate and first-year graduate students in electrical engineering and computer science, as well as researchers and professional engineers. The book is intended to be self-contained. No previous knowledge of multi-sensor data fusion is assumed, although some familiarity with the basic tools of linear algebra, calculus and simple probability theory is recommended.

Book Advances in Multi Sensor Information Fusion  Theory and Applications 2017

Download or read book Advances in Multi Sensor Information Fusion Theory and Applications 2017 written by Xue-Bo Jin and published by MDPI. This book was released on 2018-06-26 with total page 569 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "Advances in Multi-Sensor Information Fusion: Theory and Applications 2017" that was published in Sensors

Book Fundamentals of Kalman Filtering

Download or read book Fundamentals of Kalman Filtering written by Paul Zarchan and published by AIAA (American Institute of Aeronautics & Astronautics). This book was released on 2009 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Numerical basics -- Method of least squares -- Recursive least-squares filtering -- Polynomial Kalman filters -- Kalman filters in a nonpolynomial world -- Continuous polynomial Kalman filter -- Extended Kalman filtering -- Drag and falling object -- Cannon-launched projectile tracking problem -- Tracking a sine wave -- Satellite navigation -- Biases -- Linearized Kalman filtering -- Miscellaneous topics -- Fading-memory filter -- Assorted techniques for improving Kalman-filter performance -- Fixed-memory filters -- Chain-rule and least-squares filtering -- Filter bank approach to tracking a sine wave -- Appendix A: Fundamentals of Kalman-filtering software -- Appendix B: Key formula and concept summary

Book Handbook of Multisensor Data Fusion

Download or read book Handbook of Multisensor Data Fusion written by Martin Liggins II and published by CRC Press. This book was released on 2017-01-06 with total page 872 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the years since the bestselling first edition, fusion research and applications have adapted to service-oriented architectures and pushed the boundaries of situational modeling in human behavior, expanding into fields such as chemical and biological sensing, crisis management, and intelligent buildings. Handbook of Multisensor Data Fusion: Theory and Practice, Second Edition represents the most current concepts and theory as information fusion expands into the realm of network-centric architectures. It reflects new developments in distributed and detection fusion, situation and impact awareness in complex applications, and human cognitive concepts. With contributions from the world’s leading fusion experts, this second edition expands to 31 chapters covering the fundamental theory and cutting-edge developments that are driving this field. New to the Second Edition— · Applications in electromagnetic systems and chemical and biological sensors · Army command and combat identification techniques · Techniques for automated reasoning · Advances in Kalman filtering · Fusion in a network centric environment · Service-oriented architecture concepts · Intelligent agents for improved decision making · Commercial off-the-shelf (COTS) software tools From basic information to state-of-the-art theories, this second edition continues to be a unique, comprehensive, and up-to-date resource for data fusion systems designers.