<p>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 engineer
Networked multisensor decision and estimation fusion : based on advanced mathematical methods
β Scribed by Yunmin Zhu; et al
- Publisher
- CRC Press
- Year
- 2013
- Tongue
- English
- Leaves
- 431
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
''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 essential mathematical descriptions and methods for multisensory decision and estimation fusion. It covers general adapted Read more...
β¦ Table of Contents
Content: 1. Introduction --
2. Parallel statistical binary decision fusion --
3. General network statistical decision fusion --
4. Some uncertain decision combinations --
5. Convex linear estimation fusion --
6. Kalman filtering fusion --
7. Robust estimation fusion.
Abstract: ''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 essential mathematical descriptions and methods for multisensory decision and estimation fusion. It covers general adapted methods and systematic results, includes computer experiments to support the theoretical results, and fixes several popular but incorrect results in the field''
π SIMILAR VOLUMES
<p>YUNMIN ZHU In the past two decades, multi sensor or multi-source information fusion techΒ 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
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
<p><p>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
<p>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
Addressing recent challenges and developments in this growing field, <i>Multisensor Data Fusion Uncertainty Theory</i> 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