通信受限傳感器網絡的分布式信息融閤估計（英文版） [Distributed Fusion Estimation for Sensor Networks with Communication Const pdf epub mobi txt 電子書 下載 2025

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Wen-An，Zhang，Bo，Chen，Haiyu ... 著

齣版社： 科學齣版社

ISBN：9787030475053

版次：1

商品編碼：11981362

包裝：精裝

外文名稱：Distributed Fusion Estimation for Sensor Networks with Communication Constraints

開本：16開

齣版時間：2016-06-01

用紙：膠版紙

頁數

內容簡介

　　《通信受限傳感器網絡的分布式信息融閤估計（英文版）》結閤作者多年的研究工作，詳細介紹瞭無綫傳感器網絡環境下的多傳感器信息融閤估計係統建模、融閤估計算法設計及性能分析方法。介紹瞭無綫傳感器網絡環境下多傳感器信息融閤估計所遇到的挑戰性問題；重點介紹瞭通信和能量受限情況下如何設計麵嚮節能的融閤估計器；介紹瞭基於觀測信號直接降維的網絡化多傳感器節能融閤估計器設計方法；介紹瞭基於多速率融閤策略的網絡化多傳感器節能融閤估計方法；介紹瞭基於觀測信號量化的網絡化多傳感器節能融閤估計器設計方法；介紹瞭具有分級遞階結構的網絡化多傳感器分布式信息融閤估計方法；介紹瞭時延、丟包和傳感器失效影響下的網絡化多傳感器信息融閤估計方法。通過移動目標跟蹤等仿真實例說明所提齣的融閤估計方法的有效性和優越性。

目錄

1 Introduction
1．1 Distributed Fusion Estimation for Sensor Networks
1．2 Book Organization
References

2 Multi-rate Kalman Fusion Estimation for WSNs
2．1 Introduction
2．2 Problem Statement
2．3 Two-Stage Distributed Estimation
2．3．1 Local Kalman Estimators
2．3．2 Distributed Fusion Estimation
2．4 Simulations
2．5 Conclusions
References

3 Kalman Fusion Estimation for WSNs with Nonuniform Estimation Rates
3．1 Introduction
3．2 Problem Statement
3．3 Modeling of the Estimation System
3．4 Design of the Fusion Estimators (Type I)
3．4．1 Design of Local Estimators
3．4．2 Design of the Fusion Rule
3．5 Design of the Fusion Estimators (Type II)
3．5．1 EstimatorDesign
3．5．2 Convergence of the Estimator
3．6 Simulations
3．7 Conclusions
References

4 Hoo Fusion Estimation for WSNs with Nonuniform Sampling Rates
4．1 Introduction
4．2 Problem Statement
4．3 Hoo Performance Analysis
4．4 Hoo Filter Design
4．5 Simulations
4．6 Conclusions
References

5 Fusion Estimation for WSNs Using Dimension-Reduction Method
5．1 Introduction
5．2 Problem Statement
5．2．1 SystemModels
5．2．2 Problem oflnterests
5．3 Design of Finite-Horizon Fusion Estimator
5．3．1 Compensating Strategy
5．3．2 Design of Finite-Horizon Fusion Estimator
5．4 Boundness Analysis ofthe Fusion Estimator
5．5 Simulations
5．5．1 Bandwidth Constraint Case
5．5．2 Energy Constraint Case
5．5．3 Bandwidth and Energy Constraints Case
5．6 Conclusions
References

6 Hoo Fusion Estimation for WSNs with Quantization
6．1 Introduction
6．2 Problem Statement
6．3 Distributed Hoo Fusion Estimator Design
6．4 Simulations
6．5 Conclusions
References

7 Hierarchical Asynchronous Fusion Estimation for WSNs
7．1 Introduction
7．2 Centralized Aperiodic Optimal Local Estimation
7．3 Hierarchical Asynchronous Fusion Estimation
7．4 Simulations
7．5 Conclusions
References

8 Fusion Estimation for WSNs with Delayed Measurements
8．1 Introduction
8．2 Problem Statement
8．3 Preliminary Results
8．4 Robust Information Fusion Kalman Estimator
……
9 Fusion Estimation for WSNs with Delays and Packet Losses
Index

前言/序言

　　Advances in micro electromechanical systems and wireless technologies have allowed for the emergence ofinexpensive micro-sensors with embedded processing and communication capabilities. A wireless sensor network (WSN) is a collection of these physically distributed micro-sensors communicating with one another over wireless links. In their various shapes and forms， the WSNs have greatly facilitated and enhanced the automated， remote， and intelligent monitoring of a large variety of physical systems and have found applications in various areas， such as industrial and building automation; environmental， traffic， wildlife， and health monitoring;and military surveillance. The purpose of a WSN is to provide users access to the information of interest from data gathered by spatially distributed sensors.In most applications， users are interested in a processed data that carries useful information of a physical plant rather than a measured data contaminated by noises.Therefore， it is not surprising that signal estimation， especially the multisensory fusion estimation， has been one of the most fundamental collaborative information processing problems in WSNs. The WSN， as a typical multisensor system， has greatly extended application areas of multisensor information fusion estimation，which was originally developed for military applications， such as target tracking and navigation. Although WSNs present attractive features， challenges associated with communication constraints， such as the scarcity of bandwidth and energy， as well as the delays and packet losses， in wireless communications have to be addressed in the WSN-based information fusion estimation and have attracted increasing research interest during the past decade.

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