1. Introduction1.1 Network Architecture of Underwater Sensor Networks1.2 Prior Arts in Localization1.3 Underwater Weak Communication Characteristics 2. Asynchronous Localization of Underwater Sensor Networks with Mobility Prediction2.1 Introduction2.2 System Modeling and Problem Formulation2.3 Design of Asynchronous Localization Approach2.4 Performance Analysis2.4.1 Convergence2.4.2 Cramer-Rao Lower Bound2.5 Simulation2.5.1 Simulation of Active Sensor Node2.5.2 Simulation of Passive Sensor Node2.6 SummaryReferences 3. Asynchronous Localization of Underwater Sensor Networks with Consensus-Based Unscented Kalman Filtering3.1 Introduction3.2 System Modeling and Problem Formulation3.3 Design of Consensus-Based UKF Localization Approach3.4 Performance Analysis3.4.1 Observability Analysis3.4.2 Convergence Conditions3.4.3 Cramer-Rao Lower Bound3.4.4 Computational Complexity Analysis3.5 Simulation3.6 SummaryReference 4. Reinforcement Learning Based Asynchronous Localization of Underwater Sensor Networks4.1 Introduction4.2 System Modeling and Problem Formulation4.3 Design of Reinforcement Learning Based Asynchronous Localization Approach4.4 Performance Analysis4.4.1 Convergence Conditions4.4.2 Cramer-Rao Lower Bound4.4.3 Computational Complexity Analysis4.5 Simulation4.5.1 Advantage of the RL-Based Localization Strategy4.5.3 Simulation of Active Sensor Node4.5.4 Simulation of Passive Sensor Node4.6 SummaryReference 5. Privacy Preserving Asynchronous Localization of Underwater Sensor Networks5.1 Introduction5.2 System Modeling and Problem Formulation5.3 Design of Privacy Preserving Based Localization Approach5.3.1 Design of Active Sensor Node Localization Strategy5.3.2 Design of Ordinary Sensor Node Localization Strategy5.4 Performance Analysis5.4.1 Equivalence Analysis 5.4.1.1 Equivalence Analysis of Active Sensor Node 5.4.1.2 Equivalence Analysis of Ordinary Sensor Node5.4.2 Level of Privacy Preservation5.4.3 Communication Complexity Analysis5.5 Simulation5.5.1 Simulation of Active Sensor Node5.5.2 Simulation of Ordinary Sensor Node5.6 SummaryReference 6. Privacy-Preserving Asynchronous Localization of Underwater Sensor Network with Attack Detection and Ray Compensation6.1 Introduction6.2 System Modeling and Problem Formulation6.3 Design of Privacy-Preserving Localization Approach6.4 Performance Analysis6.4.1 Equivalence Analysis6.4.2 Influencing Factors of Localization Errors6.4.3 Privacy-Preserving Property6.4.4 Tradeoff Between Privacy and Transmission Cost6.5 Simulation6.6 SummaryReference 7. Deep Reinforcement Learning Based Privacy-Preserving Localization of Underwater Sensor Networks7.1 Introduction7.2 System Modeling and Problem Formulation7.3 Design of