Localization in Underwater Sensor Networks

Preface
Contents
About the Authors
Acronyms
Symbols
1 Introduction
	1.1 Underwater On-Line Monitoring System
	1.2 Localization Schemes for Wireless Sensor Networks
		1.2.1 Localization with AOA Measurements
		1.2.2 Localization with Distance-Related Measurements
			1.2.2.1 Localization with TOA Measurement
			1.2.2.2 Localization with TDOA Measurement
			1.2.2.3 Localization with RSS Measurement
			1.2.2.4 Localization with Lighthouse Approach
		1.2.3 Localization with RSS Profiling Measurements
	1.3 Unique Characteristics of USNs
	1.4 Problems Studied in This Book
	References
2 Asynchronous Localization of Underwater Sensor Networks with Mobility Prediction
	2.1 Introduction
	2.2 Network Architecture and Overview of the Localization
		2.2.1 Network Architecture
		2.2.2 Overview of the Localization
	2.3 Asynchronous Localization Approach Design
		2.3.1 Relationship Between Delay and Position
		2.3.2 Mobility Prediction for AUVs and Sensor Nodes
		2.3.3 Asynchronous Localization Optimization Problem
	2.4 Position Solving and Performance Analysis
		2.4.1 Position Solving for Sensor Nodes
		2.4.2 Convergence of the Iterative Squares Estimators
		2.4.3 Cramér-Rao Lower Bound
	2.5 Simulation Results
		2.5.1 Simulation Settings
		2.5.2 Results and Analysis
	2.6 Conclusion
	References
3 Async-Localization of USNs with Consensus-Based Unscented Kalman Filtering
	3.1 Introduction
	3.2 Network Architecture and Overview of the Localization Procedure
		3.2.1 Network Architecture
		3.2.2 Overview of the Localization Procedure
	3.3 Consensus-Based UKF Localization Approach
		3.3.1 Relationship Between Delay and Position
		3.3.2 Asynchronous Localization Optimization Problem
		3.3.3 Consensus-Based UKF Localization Algorithm
	3.4 Performance Analysis
		3.4.1 Convergence Conditions
		3.4.2 Cramér-Rao Lower Bound
		3.4.3 Error of Acoustic Wave Speed
		3.4.4 Computational Complexity Analysis
	3.5 Simulation Results
		3.5.1 Simulation Settings
		3.5.2 Results and Analysis
	3.6 Conclusion
	References
4 Reinforcement Learning-Based Asynchronous Localization of USNs
	4.1 Introduction
	4.2 System Description and Problem Formulation
	4.3 RL-Based Localization for USNs
		4.3.1 AUV-Aided Asynchronous Localization Protocol
		4.3.2 RL-Based Localization Algorithm
		4.3.3 Performance Analysis
	4.4 Simulation and Experimental Results
		4.4.1 Simulation Results
		4.4.2 Experimental Results
	4.5 Conclusion
	References
5 Privacy Preserving Asynchronous Localization of USNs
	5.1 Introduction
	5.2 Network Architecture and the Asynchronous Localization Protocol
		5.2.1 Network Architecture
		5.2.2 Asynchronous Localization Protocol
	5.3 Asynchronous Localization Algorithms
		5.3.1 PPS-Based Localization for Active Sensor
		5.3.2 PPS and PPDP Based Localization for Ordinary Sensor
		5.3.3 Consequence when There Exist Dishonest Nodes
	5.4 Performance Analyses
		5.4.1 Equivalence Analyses
		5.4.2 Level of Privacy Preservation
		5.4.3 Collision Avoidance of Packet
		5.4.4 Communication Overhead
	5.5 Simulation and Experiment Results
		5.5.1 Simulation Studies
		5.5.2 Experiment Studies
	5.6 Conclusion
	References
6 Privacy Preserving Asynchronous Localization with Attack Detection and Ray Compensation
	6.1 Introduction
	6.2 Network Model and Problem Formulation
		6.2.1 Network Architecture
		6.2.2 Clock and Stratification Models
		6.2.3 Attack and Privacy Models
		6.2.4 Problem Formulation
	6.3 Privacy-Preserving Localization for USNs
		6.3.1 Privacy-Preserving Asynchronous Transmission Protocol
		6.3.2 Privacy-Preserving Estimator with Ray Compensation
	6.4 Performance Analyses
		6.4.1 Equivalence with the Privacy-Lacking Estimation
		6.4.2 Influencing Factors of Localization Errors
		6.4.3 Privacy-Preserving Property
		6.4.4 Tradeoff Between Privacy and Transmission Cost
	6.5 Simulation and Experiment Results
		6.5.1 Simulation Studies
		6.5.2 Experimental Studies
	6.6 Conclusion
	References
7 Deep Reinforcement Learning Based Privacy Preserving Localization of USNs
	7.1 Introduction
	7.2 Network Architecture and Problem Formulation
		7.2.1 Network Architecture
		7.2.2 Adversary and Privacy Models
		7.2.3 Scenario Description
		7.2.4 Problem of Interest
	7.3 Privacy-Preserving Localization Protocol
	7.4 DRL-Based Localization Estimator
		7.4.1 Localization when All Data Is Unlabelled
		7.4.2 Localization when Labelled Data Occupies the Majority
		7.4.3 Localization when Unlabelled Data Occupies the Majority
		7.4.4 Performance Analysis
	7.5 Simulation Results
	7.6 Conclusion
	References
8 Future Research Directions
	8.1 Space-Air-Ground-Sea Network Architecture
	8.2 Intergradation Design of Localization Protocol
	8.3 Learning-Based Optimization Estimator