Download or read book Application of Kalman Filter on Multisensor Fusion Tracking written by Brian Everett Terpening and published by . This book was released on 1992 with total page 80 pages. Available in PDF, EPUB and Kindle. Book excerpt: The use of Kalman filtering in tracking targets and the reconstruction of a target's track are addressed in two separate fusion schemes. First, the Kalman filter is used to provide estimates of the position and velocity of a target based upon observations of the target's bearing. Two sensors, a radar in receive mode and an infra-red sensor, take bearings to the target at different scan rates. This information is then fused within the filter to obtain the target's track. Secondly, range, bearing, and frequency are used in fusion. Kalman filtering, Kalman smoothing, and maneuver detection are all used in the reconstruction of a target's track. Improvements are implemented in the method of forcing the excitation matrix and the results documented. fusion, Kalman filter multisensor fusion tracking.
Download or read book Multisensor Fusion Estimation Theory and Application written by Liping Yan and published by Springer Nature. This book was released on 2020-11-11 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the basic theory and methods of multisensor data fusion state estimation and its application. It consists of four parts with 12 chapters. In Part I, the basic framework and methods of multisensor optimal estimation and the basic concepts of Kalman filtering are briefly and systematically introduced. In Part II, the data fusion state estimation algorithms under networked environment are introduced. Part III consists of three chapters, in which the fusion estimation algorithms under event-triggered mechanisms are introduced. Part IV consists of two chapters, in which fusion estimation for systems with non-Gaussian but heavy-tailed noises are introduced. The book is primarily intended for researchers and engineers in the field of data fusion and state estimation. It also benefits for both graduate and undergraduate students who are interested in target tracking, navigation, networked control, etc.
Download or read book Multi sensor Multi target Data Fusion Tracking and Identification Techniques for Guidance and Control Applications written by and published by . This book was released on 1996 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Resumé på fransk.
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
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 735 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.
Download or read book Multisensor Fusion written by Anthony K. Hyder and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 929 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Springer Handbook of Robotics written by Bruno Siciliano and published by Springer. This book was released on 2016-07-27 with total page 2259 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of this handbook provides a state-of-the-art overview on the various aspects in the rapidly developing field of robotics. Reaching for the human frontier, robotics is vigorously engaged in the growing challenges of new emerging domains. Interacting, exploring, and working with humans, the new generation of robots will increasingly touch people and their lives. The credible prospect of practical robots among humans is the result of the scientific endeavour of a half a century of robotic developments that established robotics as a modern scientific discipline. The ongoing vibrant expansion and strong growth of the field during the last decade has fueled this second edition of the Springer Handbook of Robotics. The first edition of the handbook soon became a landmark in robotics publishing and won the American Association of Publishers PROSE Award for Excellence in Physical Sciences & Mathematics as well as the organization’s Award for Engineering & Technology. The second edition of the handbook, edited by two internationally renowned scientists with the support of an outstanding team of seven part editors and more than 200 authors, continues to be an authoritative reference for robotics researchers, newcomers to the field, and scholars from related disciplines. The contents have been restructured to achieve four main objectives: the enlargement of foundational topics for robotics, the enlightenment of design of various types of robotic systems, the extension of the treatment on robots moving in the environment, and the enrichment of advanced robotics applications. Further to an extensive update, fifteen new chapters have been introduced on emerging topics, and a new generation of authors have joined the handbook’s team. A novel addition to the second edition is a comprehensive collection of multimedia references to more than 700 videos, which bring valuable insight into the contents. The videos can be viewed directly augmented into the text with a smartphone or tablet using a unique and specially designed app. Springer Handbook of Robotics Multimedia Extension Portal: http://handbookofrobotics.org/
Download or read book Multisensor Fusion and Integration for Intelligent Systems written by Lee Suk-han and published by Springer Science & Business Media. This book was released on 2009-05-28 with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ?eld of multi-sensor fusion and integration is growing into signi?cance as our societyisintransitionintoubiquitouscomputingenvironmentswithroboticservices everywhere under ambient intelligence. What surround us are to be the networks of sensors and actuators that monitor our environment, health, security and safety, as well as the service robots, intelligent vehicles, and autonomous systems of ever heightened autonomy and dependability with integrated heterogeneous sensors and actuators. The ?eld of multi-sensor fusion and integration plays key role for m- ing the above transition possible by providing fundamental theories and tools for implementation. This volume is an edition of the papers selected from the 7th IEEE International Conference on Multi-Sensor Integration and Fusion, IEEE MFI‘08, held in Seoul, Korea, August 20–22, 2008. Only 32 papers out of the 122 papers accepted for IEEE MFI’08 were chosen and requested for revision and extension to be included in this volume. The 32 contributions to this volume are organized into three parts: Part I is dedicated to the Theories in Data and Information Fusion, Part II to the Multi-Sensor Fusion and Integration in Robotics and Vision, and Part III to the Applications to Sensor Networks and Ubiquitous Computing Environments. To help readers understand better, a part summary is included in each part as an introduction. The summaries of Parts I, II, and III are prepared respectively by Prof. Hanseok Ko, Prof. Sukhan Lee and Prof. Hernsoo Hahn.
Download or read book Kalman Filtering for Multi sensor Data Fusion an Application to Autonomous Navigation written by T. Coianiz and published by . This book was released on 1993 with total page 12 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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.
Download or read book Applications and Optimizations of Kalman Filter and Their Variants written by Asadullah Khalid and published by BoD – Books on Demand. This book was released on 2024-07-17 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applications and Optimizations of Kalman Filter and Their Variants is a comprehensive exploration of Kalman filters’ diverse applications and refined optimizations across various domains. It meticulously examines their role in microgrid management, offering adaptive estimation techniques for effective control strategies. The book then delves into distribution system state estimation, showcasing an innovative stochastic programming model using extended Kalman filters for reliable monitoring and control. In the realm of financial modeling, readers gain insights into how Kalman filters enhance trading strategies like pairs trading and partial co-integration, bridging finance and analytics. Moreover, the book discusses Kalman filter optimization, addressing challenges in object tracking and error reduction with techniques like dynamic stochastic approximation algorithms and M-robust estimates. With practical examples and interdisciplinary approaches, this book serves as a valuable resource for researchers, practitioners, and students looking to harness Kalman filter techniques for enhanced efficiency and accuracy across diverse fields.
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.
Download or read book Multisensor Fusion and Integration in the Wake of Big Data Deep Learning and Cyber Physical System written by Sukhan Lee and published by Springer. This book was released on 2018-07-04 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes selected papers from the 13th IEEE International Conference on Multisensor Integration and Fusion for Intelligent Systems (MFI 2017) held in Daegu, Korea, November 16–22, 2017. It covers various topics, including sensor/actuator networks, distributed and cloud architectures, bio-inspired systems and evolutionary approaches, methods of cognitive sensor fusion, Bayesian approaches, fuzzy systems and neural networks, biomedical applications, autonomous land, sea and air vehicles, localization, tracking, SLAM, 3D perception, manipulation with multifinger hands, robotics, micro/nano systems, information fusion and sensors, and multimodal integration in HCI and HRI. The book is intended for robotics scientists, data and information fusion scientists, researchers and professionals at universities, research institutes and laboratories.
Download or read book Sensor Fusion and its Applications written by Ciza Thomas and published by BoD – Books on Demand. This book was released on 2010-08-16 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to explore the latest practices and research works in the area of sensor fusion. The book intends to provide a collection of novel ideas, theories, and solutions related to the research areas in the field of sensor fusion. This book is a unique, comprehensive, and up-to-date resource for sensor fusion systems designers. This book is appropriate for use as an upper division undergraduate or graduate level text book. It should also be of interest to researchers, who need to process and interpret the sensor data in most scientific and engineering fields. The initial chapters in this book provide a general overview of sensor fusion. The later chapters focus mostly on the applications of sensor fusion. Much of this work has been published in refereed journals and conference proceedings and these papers have been modified and edited for content and style. With contributions from the world's leading fusion researchers and academicians, this book has 22 chapters covering the fundamental theory and cutting-edge developments that are driving this field.
Download or read book Dual Neural Extended Kalman Filtering Approach for Multirate Sensor Data Fusion with Industrial Applications written by Jingyi Wang and published by . This book was released on 2020 with total page 81 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Kalman filter algorithm and its variants have been widely applied to the multisensor data fusion problems to provide joint state estimation, which is more accurate than estimations from individual sensors. The performance of the Kalman filter based fusion relies on the accuracy of the models as well as process noise statistics. Deviations from correct system models and violations of noise assumptions may lead to unsatisfied sensor fusion results and even divergence. Two types of measurements are typically utilized to estimate process quality variables. One is frequent measurements, which are available at a fast and regular sampling rate but suffer from lower accuracy and higher measurement noises. The other type is infrequent measurements that are available at a slower sampling rate. The infrequent measurements, such as lab analysis results, have less availability but higher accuracy and are usually used as references to improve state estimation. The objective of this thesis is to develop new multirate sensor data fusion algorithms that can compensate for model inaccuracies and violations of noise assumption to improve the online sensor fusion performance. To fulfill this objective, a dual neural extended Kalman filter (DNEKF) algorithm is proposed by employing two neural networks to improve state estimation and output predictions. Using both frequent and infrequent measurements enables the DNEKF to provide more reliable training for the neural networks and hence to provide more robust and reliable sensor fusion results. Additionally, infrequent measurements are usually subject to irregular sampling rate and time-varying time delays. To address these problems while preserving the estimation accuracy, a fusion method that fuses frequent DNEKF estimates with infrequent estimates from the state model compensation NEKF (SNEKF) is proposed. In this approach, frequent and infrequent estimates are fused in the fusion center when the delayed infrequent measurements arrive. The weights and biases of the state model compensation neural network (SNN) are shared between the two synchronized estimation processes. In the primary separation cell (PSC) used for oil sands bitumen extraction, the interface level estimation is based on various sensors. Image processing based computer vision system, which uses a camera to capture sight glass vision frames, is considered to be the most accurate among these sensors. Although the accuracy of computer vision interface level estimation is high, its qualities are influenced by abnormalities, such as vision blocking, stains, and level transition between sight glasses. Under such abnormal scenarios, a sensor fusion strategy, which adaptively updates the fusion parameters, is proposed and integrated with the image processing based computer vision system. The performance of the proposed fault-tolerant multirate sensor fusion algorithms is demonstrated using numerical examples and case studies with industrial process data. The factory acceptance test (FAT) was conducted for the sensor fusion and computer vision integrated system in the computer process control (CPC) industrial research chair (IRC) lab under industrial environmental conditions and it demonstrated the improved estimation accuracy under various process abnormalities.
Download or read book Multisensor Data Fusion written by Hassen Fourati and published by CRC Press. This book was released on 2017-12-19 with total page 628 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multisensor Data Fusion: From Algorithms and Architectural Design to Applications covers the contemporary theory and practice of multisensor data fusion, from fundamental concepts to cutting-edge techniques drawn from a broad array of disciplines. Featuring contributions from the world’s leading data fusion researchers and academicians, this authoritative book: Presents state-of-the-art advances in the design of multisensor data fusion algorithms, addressing issues related to the nature, location, and computational ability of the sensors Describes new materials and achievements in optimal fusion and multisensor filters Discusses the advantages and challenges associated with multisensor data fusion, from extended spatial and temporal coverage to imperfection and diversity in sensor technologies Explores the topology, communication structure, computational resources, fusion level, goals, and optimization of multisensor data fusion system architectures Showcases applications of multisensor data fusion in fields such as medicine, transportation's traffic, defense, and navigation Multisensor Data Fusion: From Algorithms and Architectural Design to Applications is a robust collection of modern multisensor data fusion methodologies. The book instills a deeper understanding of the basics of multisensor data fusion as well as a practical knowledge of the problems that can be faced during its execution.
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.
