Multi-Sensor Filtering Fusion with Censored Data under a Constrained Network Environment / Hang Geng, Zidong Wang, and Yuhua Cheng.

Format:

Book

Author/Creator:

Geng, Hang, author.

Wang, Zidong, 1966- author.

Cheng, Yuhua, author.

Language:

English

Subjects (All):

Sensor networks.

Multisensor data fusion.

Physical Description:

1 online resource (263 pages)

Edition:

First edition.

Place of Publication:

Boca Raton, FL : CRC Press, [2025]

Summary:

This book presents the up-to-date research developments and novel methodologies on Multi-sensor filtering fusion (MSFF) for a class of complex systems subject to censored data under a constrained network environment.

Contents:

Cover

Half Title

Title

Copyright

Dedication

Contents

List of Figures

List of Tables

List of Symbols

Preface

Acknowledgement

Foreword

List of Contributors

Chapter 1 Introduction

1.1 Canonical MSFF Schemes

1.1.1 Centralized Filtering Fusion

1.1.2 Information Filtering Fusion

1.1.3 Sequential Filtering Fusion

1.1.4 Weighted Filtering Fusion

1.1.5 Covariance Intersection Fusion

1.1.6 Federated Filtering Fusion

1.2 Censored Measurements

1.2.1 One-Side Censored Measurements

1.2.2 Two-Side Censored Measurements

1.2.3 Kalman Filtering with Censored Measurements

1.3 Communication Constraints

1.3.1 Communication Delays

1.3.2 Fading Measurements

1.3.3 Nonlinear Disturbances

1.3.4 Quantized Measurements

1.3.5 Disordered Measurements

1.4 Outline

Chapter 2 Optimal Filtering for Networked Systems with Channel Fading and Measurement Censoring

2.1 Problem Formulation

2.2 Tobit Kalman Filter with Fading Measurements

2.3 Illustrative Examples

2.3.1 Oscillator Example

2.3.2 Radar Tracking Example

2.4 Summary

Chapter 3 Tobit Kalman Filter with Time-Correlated Multiplicative Sensor Noises under Redundant Channel Transmission

3.1 Problem Formulation

3.2 State-Dependent TKF under Redundant Channels

3.3 An Illustrative Example

3.4 Summary

Chapter 4 State Estimation under Non-Gaussian Lévy and Time-Correlated Additive Sensor Noises: A Modified Tobit Kalman Filtering Approach

4.1 Problem Formulation

4.2 A Modified Tobit Kalman Filter

4.3 An Illustrative Example

4.4 Summary

Chapter 5 Protocol-Based Filter Design under Integral Measurements and Probabilistic Sensor Failures: The Censored Data Case

5.1 Problem Formulation

5.2 Protocol-Based Tobit Kalman Filter

5.3 Self-Propagating Lower and Upper Bounds.

5.4 An Illustrative Example

5.5 Summary

Chapter 6 Distributed Optimal Filtering Fusion over a Packet-Delaying Network Subject to Censored Data: A Probabilistic Perspective

6.1 Problem Formulation

6.2 Distributed Federated Tobit Kalman Filter with Packet Delays

6.2.1 Local Tobit Kalman Filter with Packet Delays

6.2.2 Distributed Tobit Kalman Filter with Packet Delays

6.3 A Probabilistic Perspective

6.4 An Illustrative Example

6.5 Summary

Chapter 7 Federated Tobit Kalman Filtering Fusion with Dead-Zone-Like Censoring and Dynamical Bias under the Round-Robin Protocol

7.1 Problem Formulation

7.2 Main Results

7.3 Illustrative Examples

7.3.1 Oscillator Example

7.3.2 Distributed Target Tracking Example

7.4 Summary

Chapter 8 Multi-Sensor Filtering Fusion with Parametric Uncertainties and Measurement Censoring: Monotonicity and Boundedness

8.1 Problem Formulation

8.2 Design of the Fusion Estimator

8.3 Boundedness and Monotonicity

8.4 Illustrative Examples

8.4.1 Oscillator Example

8.4.2 Target Tracking Example

8.5 Summary

Chapter 9 Protocol-Based Fusion Estimator Design for State-Saturated Systems with Dead-Zone-Like Censoring under Deception Attacks

9.1 Problem Formulation

9.2 Main Results

9.3 An Illustrative Example

9.4 Summary

Chapter 10 Variance-Constrained Filtering Fusion for Nonlinear Cyber-Physical Systems with the Denial-of-Service Attacks and Stochastic Communication Protocol

10.1 Problem Formulation

10.2 Main Results

10.3 An Illustrative Example

10.4 Summary

Chapter 11 Conclusions and Future Topics

Bibliography

Index.

Notes:

Includes bibliographical references and index.

Description based on publisher supplied metadata and other sources.

Description based on print version record.

ISBN:

9781040106075

1040106072

9781003461623

100346162X

9781040106099

1040106099

OCLC:

1446216163