Networked Multisensor Decision and Estimation Fusion: Based on Advanced Mathematical Methods

✍ Scribed by Yunmin Zhu (Author); Jie Zhou (Author); Xiaojing Shen (Author); Enbin Song (Author); Yingting Luo (Author)

Publisher: CRC Press
Year: 2012
Leaves: 440
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

Due to the increased capability, reliability, robustness, and survivability of systems with multiple distributed sensors, multi-source information fusion has become a crucial technique in a growing number of areas-including sensor networks, space technology, air traffic control, military engineering, agriculture and environmental engineering, and i

✦ Table of Contents

Introduction. Parallel Statistical Binary Decision Fusion. General Network Statistical Decision Fusion. Some Uncertain Decision Combination. Convex Linear Estimation Fusion. Kalman Filtering Fusion. Robust Estimation Fusion. References.

✦ Subjects

Engineering & Technology;Electrical & Electronic Engineering;Instrumentation, Measurement & Testing;Systems & Controls;Mathematics & Statistics for Engineers

📜 SIMILAR VOLUMES

Networked multisensor decision and estim

📁 Networked multisensor decision and estimation fusion : based on advanced mathematical methods

✍ Yunmin Zhu; et al 📂 Library 📅 2013 🏛 CRC Press 🌐 English

''Multisource information fusion has become a crucial technique in areas such as sensor networks, space technology, air traffic control, military engineering, communications, industrial control, agriculture, and environmental engineering. Exploring recent signficant results, this book presents essen

Multisensor Decision And Estimation Fusi

📁 Multisensor Decision And Estimation Fusion

✍ Yunmin Zhu (auth.) 📂 Library 📅 2003 🏛 Springer US 🌐 English

YUNMIN ZHU In the past two decades, multi sensor or multi-source information fusion tech niques have attracted more and more attention in practice, where observations are processed in a distributed manner and decisions or estimates are made at the individual processors, and processed data (or co

Multisensor Fusion Estimation Theory and

📁 Multisensor Fusion Estimation Theory and Application

✍ Liping Yan, Lu Jiang, Yuanqing Xia 📂 Library 📅 2020 🏛 Springer Singapore 🌐 English

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 syste

Multisensor Fusion Estimation Theory and

📁 Multisensor Fusion Estimation Theory and Application

✍ Liping Yan, Lu Jiang, Yuanqing Xia 📂 Library 📅 2021 🏛 Springer Singapore;Springer 🌐 English

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

Multisensor Fusion

📁 Multisensor Fusion

✍ R. Von Hanwehr (auth.), A. K. Hyder, E. Shahbazian, E. Waltz (eds.) 📂 Library 📅 2002 🏛 Springer Netherlands 🌐 English

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

Uncertainty Theories and Multisensor Dat

📁 Uncertainty Theories and Multisensor Data Fusion

✍ Alain Appriou 📂 Library 📅 2014 🏛 Wiley-ISTE 🌐 English

Addressing recent challenges and developments in this growing field, Multisensor Data Fusion Uncertainty Theory first discusses basic questions such as: Why and when is multiple sensor fusion necessary? How can the available measurements be characterized in such a case? What is the purpose an