Statistical Sensor Fusion

Statistical Sensor Fusion
Author: Fredrik Gustafsson
Publisher:
Total Pages: 532
Release: 2010
Genre: Algoritmer / sao
ISBN: 9789144054896

Sensor fusion deals with Merging information from two or more sensors. Elsewhere the area of statistical signal processing provides a powerful toolbox to attack bothering theoretical and practical problems. The objective of this book is to explain state of the art theory and algorithms into statistical sensor fusion, covering estimation, detection and non-linear filtering theory with applications to localisation, navigation and tracking problems. The book starts with a review of the theory on linear and non-linear estimation, with a focus on sensor network applications. Then, general non-linear filter theory is surveyed with a Particular attention to Different variants of the Kalman filter and the particle filter. Complexity and implementation issues are discussed in detail. Simultaneous localisation and mapping (SLAM) is distressed as a challenging application area of high-dimensional non-linear filtering problems. The book spans the whole range from mathematical foundations provided in Extensive Appendices, to real-world problems the covered in a party surveying standard sensors, motion models and applications in this field. All models and algorithms are available as object-oriented Matlab code with an Extensive data file library, and the examples, Which are richly distressed to illustrate the theory, are supplemented by fully reproducible Matlab code.

Multisensor Data Fusion

Multisensor Data Fusion
Author: Hassen Fourati
Publisher: CRC Press
Total Pages: 628
Release: 2017-12-19
Genre: Technology & Engineering
ISBN: 1351830880

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.

Sensor and Data Fusion

Sensor and Data Fusion
Author: Lawrence A. Klein
Publisher: SPIE Press
Total Pages: 346
Release: 2004
Genre: Technology & Engineering
ISBN: 9780819454355

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.

Handbook of Multisensor Data Fusion

Handbook of Multisensor Data Fusion
Author: Martin Liggins II
Publisher: CRC Press
Total Pages: 872
Release: 2017-01-06
Genre: Technology & Engineering
ISBN: 1420053094

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.

Sensor and Data Fusion Concepts and Applications

Sensor and Data Fusion Concepts and Applications
Author: Lawrence A. Klein
Publisher: SPIE-International Society for Optical Engineering
Total Pages: 256
Release: 1999
Genre: Technology & Engineering
ISBN:

First published in 1993, this Tutorial Text has been revised and updated to provide explanations and examples of data fusion algorithms in areas not covered in the first edition. These include Bayesian inference, artificial neural networks and fuzzy logic. All of the chapters in the first edition have been revised and updated and new material is included on the FASCODE and MODTRAN atmospheric models, and EOSAEL, which analyzes physical processes that affect the performance of millimeter-wave and IR sensors.

Multi-Sensor Data Fusion with MATLAB

Multi-Sensor Data Fusion with MATLAB
Author: Jitendra R. Raol
Publisher: CRC Press
Total Pages: 570
Release: 2009-12-16
Genre: Technology & Engineering
ISBN: 1439800057

Using MATLAB examples wherever possible, Multi-Sensor Data Fusion with MATLAB explores the three levels of multi-sensor data fusion (MSDF): kinematic-level fusion, including the theory of DF; fuzzy logic and decision fusion; and pixel- and feature-level image fusion. The authors elucidate DF strategies, algorithms, and performance evaluation mainly

Mathematical Techniques in Multisensor Data Fusion

Mathematical Techniques in Multisensor Data Fusion
Author: David Lee Hall
Publisher: Artech House
Total Pages: 470
Release: 2004
Genre: Computers
ISBN: 9781580533355

Since the publication of the first edition of this book, advances in algorithms, logic and software tools have transformed the field of data fusion. The latest edition covers these areas as well as smart agents, human computer interaction, cognitive aides to analysis and data system fusion control. data fusion system, this book guides you through the process of determining the trade-offs among competing data fusion algorithms, selecting commercial off-the-shelf (COTS) tools, and understanding when data fusion improves systems processing. Completely new chapters in this second edition explain data fusion system control, DARPA's recently developed TRIP model, and the latest applications of data fusion in data warehousing and medical equipment, as well as defence systems.

Multi-Sensor Data Fusion

Multi-Sensor Data Fusion
Author: H.B. Mitchell
Publisher: Springer Science & Business Media
Total Pages: 281
Release: 2007-07-13
Genre: Technology & Engineering
ISBN: 3540715592

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.